From 9a3600462bfb88f18c17ee46c7a91bb5b82d3fb9 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Thu, 27 Mar 2025 07:15:31 +0000 Subject: [PATCH 01/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 1deeeeb..7f7ac3f 100644 --- a/lib/main.js +++ b/lib/main.js @@ -26,7 +26,7 @@ var indicesComplement = require( '@stdlib/array-base-indices-complement' ); var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From bb2c1113fded6f259a37d34f775e319d0f947b2a Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Thu, 27 Mar 2025 07:16:33 +0000 Subject: [PATCH 02/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 52 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/index.js | 35 - dist/index.js.map | 7 - docs/repl.txt | 86 - examples/index.js | 50 - index.mjs | 4 + index.mjs.map | 1 + lib/0d.js | 92 - lib/0d_accessors.js | 97 - lib/1d.js | 140 - lib/1d_accessors.js | 149 - lib/2d.js | 166 - lib/2d_accessors.js | 174 - lib/2d_blocked.js | 200 - lib/2d_blocked_accessors.js | 208 - lib/3d.js | 178 - lib/factory.js | 118 - lib/increment_offsets.js | 46 - lib/index.js | 145 - lib/initialize_array_views.js | 57 - lib/main.js | 338 -- lib/nd.js | 150 - lib/nd_accessors.js | 158 - lib/offsets.js | 42 - lib/set_view_offsets.js | 52 - package.json | 70 +- stats.html | 4842 ++++++++++++++++++ test/dist/test.js | 33 - test/test.js | 35 - 54 files changed, 4876 insertions(+), 6186 deletions(-) delete mode 100644 .editorconfig delete mode 100644 .eslintrc.js delete mode 100644 .gitattributes delete mode 100644 .github/PULL_REQUEST_TEMPLATE.md delete mode 100644 .github/workflows/cancel.yml delete mode 100644 .github/workflows/close_pull_requests.yml delete mode 100644 .github/workflows/examples.yml delete mode 100644 .github/workflows/npm_downloads.yml delete mode 100644 .github/workflows/productionize.yml delete mode 100644 .github/workflows/publish.yml delete mode 100644 .github/workflows/test.yml delete mode 100644 .github/workflows/test_bundles.yml delete mode 100644 .github/workflows/test_coverage.yml delete mode 100644 .github/workflows/test_install.yml delete mode 100644 .github/workflows/test_published_package.yml delete mode 100644 .gitignore delete mode 100644 .npmignore delete mode 100644 .npmrc delete mode 100644 CHANGELOG.md delete mode 100644 CITATION.cff delete mode 100644 CODE_OF_CONDUCT.md delete mode 100644 CONTRIBUTING.md delete mode 100644 Makefile delete mode 100644 SECURITY.md delete mode 100644 branches.md delete mode 100644 dist/index.js delete mode 100644 dist/index.js.map delete mode 100644 docs/repl.txt delete mode 100644 examples/index.js create mode 100644 index.mjs create mode 100644 index.mjs.map delete mode 100644 lib/0d.js delete mode 100644 lib/0d_accessors.js delete mode 100644 lib/1d.js delete mode 100644 lib/1d_accessors.js delete mode 100644 lib/2d.js delete mode 100644 lib/2d_accessors.js delete mode 100644 lib/2d_blocked.js delete mode 100644 lib/2d_blocked_accessors.js delete mode 100644 lib/3d.js delete mode 100644 lib/factory.js delete mode 100644 lib/increment_offsets.js delete mode 100644 lib/index.js delete mode 100644 lib/initialize_array_views.js delete mode 100644 lib/main.js delete mode 100644 lib/nd.js delete mode 100644 lib/nd_accessors.js delete mode 100644 lib/offsets.js delete mode 100644 lib/set_view_offsets.js create mode 100644 stats.html delete mode 100644 test/dist/test.js delete mode 100644 test/test.js diff --git a/.editorconfig b/.editorconfig deleted file mode 100644 index dab5d2a..0000000 --- a/.editorconfig +++ /dev/null @@ -1,180 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. 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However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. 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-# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index c9fa4fb..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var N=function(s,r){return function(){return r||s((r={exports:{}}).exports,r),r.exports}};var T=N(function(Te,K){ -function Or(s,r){var e,n;for(n=2;n0;){for(y0;){for(g0;){for(g0;){for(w3?u=n:u={},j=r.length,a=[],O=0;Of)throw new RangeError(C("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",f,A(e,",")));for(o=f-S,O=1;O2?f=q:f={},De(s,e,n,f)}}xr.exports=_e -});var Ue=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ye=br();Ue(yr,"factory",Ye);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 1db39ee..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..0617357 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,s){var e;for(e=0;e0;){for(k0;){for(N0;){for(z0;){for(k3?u:{},K=a.length,z=[],S=0;Sp)throw new RangeError(d("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",p,i(l,",")));for(M=p-L,S=1;S2?n:{};return z(r,s,e,t)}}r(z,"factory",T);export{z as default,T as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..e4c44d2 --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index c59389c..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 7f7ac3f..0000000 --- a/lib/main.js +++ /dev/null @@ -1,338 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( x.accessorProtocol || y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index f7cdc26..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ j ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..4db6952 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 9cc2086261e8edadf3a3fd8e209fd5f428148e39 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Thu, 27 Mar 2025 07:37:59 +0000 Subject: [PATCH 03/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 24438f2..15d2749 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 5be7df1054fafc3696dc9fccf999e65796618486 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Thu, 27 Mar 2025 07:38:20 +0000 Subject: [PATCH 04/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 0617357..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,s){var e;for(e=0;e0;){for(k0;){for(N0;){for(z0;){for(k3?u:{},K=a.length,z=[],S=0;Sp)throw new RangeError(d("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",p,i(l,",")));for(M=p-L,S=1;S2?n:{};return z(r,s,e,t)}}r(z,"factory",T);export{z as default,T as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index e4c44d2..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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-# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 56a4272..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var N=function(s,r){return function(){return r||s((r={exports:{}}).exports,r),r.exports}};var T=N(function(Be,K){ -function Or(s,r){var e,n;for(n=2;n0;){for(y0;){for(g0;){for(g0;){for(w3?v=n:v={},j=r.length,a=[],O=0;Of)throw new RangeError(C("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",f,A(e,",")));for(u=f-S,O=1;O2?f=q:f={},_e(s,e,n,f)}}xr.exports=Ue -});var Ye=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ke=br();Ye(yr,"factory",Ke);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 91eadc4..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || numel( shc ) === 0 ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"blockedaccessorunary2d", "blockedunary2d", "accessorunary0d", "accessorunary1d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..c8495cf --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,s){var e;for(e=0;e0;){for(k0;){for(N0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sp)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",p,d(u,",")));for(M=p-L,S=1;S2?n:{};return z(r,s,e,t)}}r(z,"factory",T);export{z as default,T as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..34ad8fc --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || numel( shc ) === 0 ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index c59389c..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 15d2749..0000000 --- a/lib/main.js +++ /dev/null @@ -1,339 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || numel( shc ) === 0 ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( x.accessorProtocol || y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index f7cdc26..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ j ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..d3f20e6 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 56512b1ec84ce5bdc0ae079380268ef680da5eba Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 02:18:27 +0000 Subject: [PATCH 06/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index d6007a1..5888290 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 052fa8bc96c1153fd125d336ee76932d80b89c67 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 02:18:49 +0000 Subject: [PATCH 07/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index c8495cf..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,s){var e;for(e=0;e0;){for(k0;){for(N0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sp)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",p,d(u,",")));for(M=p-L,S=1;S2?n:{};return z(r,s,e,t)}}r(z,"factory",T);export{z as default,T as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index 34ad8fc..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || numel( shc ) === 0 ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': 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-# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 770d688..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var N=function(s,r){return function(){return r||s((r={exports:{}}).exports,r),r.exports}};var T=N(function(Be,K){ -function Or(s,r){var e,n;for(n=2;n0;){for(y0;){for(g0;){for(g0;){for(w3?v=n:v={},j=r.length,a=[],O=0;Of)throw new RangeError(C("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",f,A(e,",")));for(u=f-S,O=1;O2?f=q:f={},_e(s,e,n,f)}}xr.exports=Ue -});var Ye=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ke=br();Ye(yr,"factory",Ke);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 73f09e0..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"blockedaccessorunary2d", "blockedunary2d", "accessorunary0d", "accessorunary1d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..97a5079 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function v(r,s){var e;for(e=0;e0;){for(k0;){for(N0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sp)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",p,d(u,",")));for(M=p-L,S=1;S2?n:{};return z(r,s,e,t)}}r(z,"factory",T);export{z as default,T as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..e0942a0 --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index c59389c..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 5888290..0000000 --- a/lib/main.js +++ /dev/null @@ -1,434 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( x.accessorProtocol || y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( x.accessorProtocol || y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( x.accessorProtocol || y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index f7cdc26..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ j ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..b39a1f0 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 970503b92fc47858a2a0cd5ead50b3512b4d50ce Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 06:37:16 +0000 Subject: [PATCH 09/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index d5052e0..571a4a6 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 50d2d68bd00ad50a3a45a6c89219807fd1d05712 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 06:37:38 +0000 Subject: [PATCH 10/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 97a5079..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function v(r,s){var e;for(e=0;e0;){for(k0;){for(N0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sp)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",p,d(u,",")));for(M=p-L,S=1;S2?n:{};return z(r,s,e,t)}}r(z,"factory",T);export{z as default,T as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index e0942a0..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( x.accessorProtocol || y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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-# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 769910c..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var N=function(i,r){return function(){return r||i((r={exports:{}}).exports,r),r.exports}};var T=N(function(Be,K){ -function Or(i,r){var e,o;for(o=2;o0;){for(y0;){for(g0;){for(g0;){for(w3?v=o:v={},j=r.length,a=[],O=0;Of)throw new RangeError(M("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",f,C(e,",")));for(u=f-S,O=1;O2?f=q:f={},_e(i,e,o,f)}}xr.exports=Ue -});var Ye=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ke=br();Ye(yr,"factory",Ke);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 4cfbf71..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..2c33f12 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function v(r,e){var s;for(s=0;s0;){for(k0;){for(N0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",T);export{z as default,T as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..246bf2a --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index c59389c..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 571a4a6..0000000 --- a/lib/main.js +++ /dev/null @@ -1,434 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index f7cdc26..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ j ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..a8e3624 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 5ceae992cc2ecd65ce8251674c50b2c25738c862 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 07:27:47 +0000 Subject: [PATCH 12/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 466911a..5d660e9 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From dd1cabe99662fe3a4d488d1d8c97cc1c0d961dd5 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 07:28:05 +0000 Subject: [PATCH 13/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 2c33f12..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function v(r,e){var s;for(s=0;s0;){for(k0;){for(N0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",T);export{z as default,T as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index 246bf2a..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.', ndims, M, i, arr[ i ].shape.length ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a 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-# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index a22d391..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var V=function(i,r){return function(){return r||i((r={exports:{}}).exports,r),r.exports}};var T=V(function(Be,K){ -function Or(i,r){var e,o;for(o=2;o0;){for(y0;){for(g0;){for(g0;){for(w3?v=o:v={},j=r.length,a=[],O=0;Of)throw new RangeError(I("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",f,A(e,",")));for(u=f-N,O=1;O2?f=q:f={},_e(i,e,o,f)}}xr.exports=Ue -});var Ye=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ke=br();Ye(yr,"factory",Ke);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 17be6ba..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), M, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"blockedaccessorunary2d", "blockedunary2d", "accessorunary0d", "accessorunary1d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..386a11a --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..affc7fd --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), M, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index c59389c..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 5d660e9..0000000 --- a/lib/main.js +++ /dev/null @@ -1,434 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), M, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index f7cdc26..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ j ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..3567b92 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 6f72fb4519909673d1f9704283f1d5b838f2d24c Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 07:31:00 +0000 Subject: [PATCH 15/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index dc4bb07..6b3d627 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 8ab589e4baf7cd9d519affcbd8c67a719f1dbc99 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 30 Mar 2025 07:31:19 +0000 Subject: [PATCH 16/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 386a11a..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index affc7fd..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), M, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a 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-# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 096799c..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var V=function(i,r){return function(){return r||i((r={exports:{}}).exports,r),r.exports}};var T=V(function(Be,K){ -function Or(i,r){var e,o;for(o=2;o0;){for(y0;){for(g0;){for(g0;){for(w3?v=o:v={},j=r.length,a=[],O=0;Of)throw new RangeError(I("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",f,A(e,",")));for(u=f-N,O=1;O2?f=q:f={},_e(i,e,o,f)}}xr.exports=Ue -});var Ye=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ke=br();Ye(yr,"factory",Ke);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 181b5a1..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"blockedaccessorunary2d", "blockedunary2d", "accessorunary0d", "accessorunary1d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..9363fd0 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..92b45d7 --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index c59389c..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 6b3d627..0000000 --- a/lib/main.js +++ /dev/null @@ -1,434 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index f7cdc26..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ j ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..6fe0dab --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 74595492e9a4b3e0000fdc89dc19afd37186ab30 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 1 Apr 2025 07:04:58 +0000 Subject: [PATCH 18/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index dc4bb07..6b3d627 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 9c6c80708b093f4ae0f3873523c2b178deae2169 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 1 Apr 2025 07:05:21 +0000 Subject: [PATCH 19/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 9363fd0..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index 92b45d7..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a 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-# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. 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We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index c41d225..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var V=function(i,r){return function(){return r||i((r={exports:{}}).exports,r),r.exports}};var T=V(function(Be,K){ -function Or(i,r){var e,o;for(o=2;o0;){for(y0;){for(g0;){for(g0;){for(w3?v=o:v={},j=r.length,a=[],O=0;Of)throw new RangeError(I("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",f,A(e,",")));for(u=f-N,O=1;O2?f=q:f={},_e(i,e,o,f)}}xr.exports=Ue -});var Ye=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ke=br();Ye(yr,"factory",Ke);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 5234cdf..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"blockedaccessorunary2d", "blockedunary2d", "accessorunary0d", "accessorunary1d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..9363fd0 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..edc4347 --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10_blocked_accessors.js b/lib/10_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index aa26161..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index aa0f4c9..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index 3cff64f..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index d06bf95..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 8c8d2f8..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index bf57509..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index ca45081..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index a1ba021..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index efb1480..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index a615dcc..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index e34e82c..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 96bc45f..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 0c56b4b..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 9a7cdd0..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 7882249..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index b6129f5..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 6b3d627..0000000 --- a/lib/main.js +++ /dev/null @@ -1,434 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index f7cdc26..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ j ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..754953f --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From a833109903eede124eebf4d405eebbd93c619136 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sat, 5 Apr 2025 09:29:51 +0000 Subject: [PATCH 21/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index dc4bb07..6b3d627 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedunary2d = require( './2d_blocked.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From be616e00409c056f884805a60dbb04d13d557bf9 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sat, 5 Apr 2025 09:30:13 +0000 Subject: [PATCH 22/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 9363fd0..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index edc4347..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ j ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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-# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. 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We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 98033be..0000000 --- a/dist/index.js +++ /dev/null @@ -1,35 +0,0 @@ -"use strict";var V=function(i,r){return function(){return r||i((r={exports:{}}).exports,r),r.exports}};var T=V(function(Be,K){ -function Or(i,r){var e,o;for(o=2;o0;){for(y0;){for(g0;){for(g0;){for(w3?v=o:v={},j=r.length,a=[],O=0;Of)throw new RangeError(I("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",f,A(e,",")));for(u=f-N,O=1;O2?f=q:f={},_e(i,e,o,f)}}xr.exports=Ue -});var Ye=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),yr=Y(),Ke=br();Ye(yr,"factory",Ke);module.exports=yr; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 215cd66..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"blockedaccessorunary2d", "blockedunary2d", "accessorunary0d", "accessorunary1d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..58bc92f --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..ef6582a --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10_blocked_accessors.js b/lib/10_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index aa26161..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index aa0f4c9..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index 3cff64f..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index d06bf95..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 8c8d2f8..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index bf57509..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index ca45081..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index a1ba021..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index efb1480..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index a615dcc..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index e34e82c..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 96bc45f..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 0c56b4b..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 9a7cdd0..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 7882249..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index b6129f5..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 6b3d627..0000000 --- a/lib/main.js +++ /dev/null @@ -1,434 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - null, // unary4d, - null, // unary5d, - null, // unary6d, - null, // unary7d, - null, // unary8d, - null, // unary9d, - null // unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - null, // accessorunary2d, - null, // accessorunary3d, - null, // accessorunary4d, - null, // accessorunary5d, - null, // accessorunary6d, - null, // accessorunary7d, - null, // accessorunary8d, - null, // accessorunary9d, - null // accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - null, // blockedunary3d, - null, // blockedunary4d, - null, // blockedunary5d, - null, // blockedunary6d, - null, // blockedunary7d, - null, // blockedunary8d, - null, // blockedunary9d, - null // blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - null, // blockedaccessorunary3d, - null, // blockedaccessorunary4d, - null, // blockedaccessorunary5d, - null, // blockedaccessorunary6d, - null, // blockedaccessorunary7d, - null, // blockedaccessorunary8d, - null, // blockedaccessorunary9d, - null // blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..754953f --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 98fc7bcf5ddd06003dce60a6f8015d7a72a5535d Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Fri, 11 Apr 2025 03:30:30 +0000 Subject: [PATCH 24/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 0acc5e7..d5781dc 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From c51977c107f808fb1508087878a0fd9b4c9d00d7 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Fri, 11 Apr 2025 03:31:21 +0000 Subject: [PATCH 25/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 58bc92f..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function g(r,e){var s;for(s=0;s0;){for(k0;){for(P0;){for(z0;){for(k3?f:{},K=l.length,z=[],S=0;Sc)throw new RangeError(a("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,d(u,",")));for(M=c-L,S=1;S2?n:{};return z(r,e,s,t)}}r(z,"factory",A);export{z as default,A as factory}; -//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map deleted file mode 100644 index ef6582a..0000000 --- a/index.mjs.map +++ /dev/null @@ -1 +0,0 @@ -{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_blocked.js","../lib/2d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tnull, // unary4d,\n\tnull, // unary5d,\n\tnull, // unary6d,\n\tnull, // unary7d,\n\tnull, // unary8d,\n\tnull, // unary9d,\n\tnull // unary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\tnull, // accessorunary2d,\n\tnull, // accessorunary3d,\n\tnull, // accessorunary4d,\n\tnull, // accessorunary5d,\n\tnull, // accessorunary6d,\n\tnull, // accessorunary7d,\n\tnull, // accessorunary8d,\n\tnull, // accessorunary9d,\n\tnull // accessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tnull, // blockedunary3d,\n\tnull, // blockedunary4d,\n\tnull, // blockedunary5d,\n\tnull, // blockedunary6d,\n\tnull, // blockedunary7d,\n\tnull, // blockedunary8d,\n\tnull, // blockedunary9d,\n\tnull // blockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tnull, // blockedaccessorunary3d,\n\tnull, // blockedaccessorunary4d,\n\tnull, // blockedaccessorunary5d,\n\tnull, // blockedaccessorunary6d,\n\tnull, // blockedaccessorunary7d,\n\tnull, // blockedaccessorunary8d,\n\tnull, // blockedaccessorunary9d,\n\tnull // blockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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-# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. 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We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 7b6f946..0000000 --- a/dist/index.js +++ /dev/null @@ -1,99 +0,0 @@ -"use strict";var fr=function(Y,a){return function(){return a||Y((a={exports:{}}).exports,a),a.exports}};var jv=fr(function(si,Sv){ -function ne(Y,a){var w,r;for(r=2;r0;){for(t0;){for(h0;){for(f0;){for(n0;){for(d0;){for(N0;){for(y0;){for(S0;){for(g0;){for(V0;){for(z0;){for(L0;){for(D0;){for(I0;){for(M0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(P0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(h0;){for(j0;){for(n0;){for(d0;){for(c0;){for(y0;){for(S0;){for(g0;){for(x0;){for(z0;){for(L0;){for(D0;){for(I0;){for(N0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(z0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(F0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A3?m=r:m={},c=a.length,q=[],g=0;gv)throw new RangeError(ev('2AZHn',v,Cr(w,",")));for(n=v-d,g=1;g2?v=J:v={},ei(Y,w,r,v)}}ue.exports=oi -});var fi=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),se=qv(),ui=ie();fi(se,"factory",ui);module.exports=se; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 39dbb07..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunary10d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..8f1566c --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import b from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function w(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(ur0;){for(nr0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(ur0;){for(nr0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},L=n.length,y=[],U=0;Uc)throw new RangeError(d("invalid argument. 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Value: [%s].",c,p(u,",")));for(O=c-M,U=1;U2?f:{};return I(r,s,o,e)}}r(I,"factory",R);export{I as default,R as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..bd89958 --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index aa26161..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index aa0f4c9..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index dfa8260..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,149 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, dims, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index 3cff64f..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index d06bf95..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 8c8d2f8..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index bf57509..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index ca45081..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index a1ba021..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index efb1480..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index a615dcc..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index e34e82c..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 96bc45f..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 0c56b4b..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 9a7cdd0..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 7882249..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index b6129f5..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index d5781dc..0000000 --- a/lib/main.js +++ /dev/null @@ -1,466 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..09ff598 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From e957efd0759c45c6f24cc551ea492af8d52fd596 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Wed, 16 Apr 2025 04:19:06 +0000 Subject: [PATCH 27/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 0acc5e7..d5781dc 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 4786627318566cfc3e0a59c197188caadd2f0a85 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Wed, 16 Apr 2025 04:19:32 +0000 Subject: [PATCH 28/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 8f1566c..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import b from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function w(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(ur0;){for(nr0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(ur0;){for(nr0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},L=n.length,y=[],U=0;Uc)throw new RangeError(d("invalid argument. 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Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], [ 2, 3 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, dims, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index 09ff598..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From 1f47ca759959e4aa7305513a731152fdb4163e47 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Wed, 16 Apr 2025 04:20:07 +0000 Subject: [PATCH 29/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 79 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/index.js | 99 - dist/index.js.map | 7 - 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-# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -225,7 +222,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index d0f0000..0000000 --- a/dist/index.js +++ /dev/null @@ -1,99 +0,0 @@ -"use strict";var fr=function(Y,a){return function(){return a||Y((a={exports:{}}).exports,a),a.exports}};var jv=fr(function(si,Sv){ -function ne(Y,a){var w,r;for(r=2;r0;){for(t0;){for(h0;){for(f0;){for(n0;){for(d0;){for(N0;){for(y0;){for(S0;){for(g0;){for(V0;){for(z0;){for(L0;){for(D0;){for(I0;){for(M0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(P0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(h0;){for(j0;){for(n0;){for(d0;){for(c0;){for(y0;){for(S0;){for(g0;){for(b0;){for(z0;){for(L0;){for(D0;){for(I0;){for(N0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(z0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(F0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A3?m=r:m={},c=a.length,q=[],g=0;gv)throw new RangeError(ev('2AZHn',v,Cr(w,",")));for(n=v-d,g=1;g2?v=J:v={},ei(Y,w,r,v)}}ue.exports=oi -});var fi=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),se=qv(),ui=ie();fi(se,"factory",ui);module.exports=se; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 0c20c14..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 42a0d2b..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing subarray from the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..4ccc56b --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function b(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},K=u.length,y=[],S=0;Sc)throw new RangeError(d("invalid argument. 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Value: [%s].",c,p(n,",")));for(M=c-L,S=1;S2?f:{};return q(r,s,o,e)}}r(q,"factory",I);export{q as default,I as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..b811d5c --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index aa26161..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index aa0f4c9..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index 3cff64f..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index d06bf95..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 8c8d2f8..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index bf57509..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index ca45081..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index a1ba021..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index efb1480..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index a615dcc..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index e34e82c..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 96bc45f..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 0c56b4b..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 9a7cdd0..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 7882249..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index b6129f5..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index d5781dc..0000000 --- a/lib/main.js +++ /dev/null @@ -1,466 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..0f06a47 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index b1cd0f1..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2021 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 1a2410a654bdef80201c2fd46e275f0c3bf78986 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Wed, 16 Apr 2025 08:48:13 +0000 Subject: [PATCH 30/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 0acc5e7..d5781dc 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 548815d7a1c6a2636152e64a1f8bbd5dd69de5d2 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Wed, 16 Apr 2025 08:48:35 +0000 Subject: [PATCH 31/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 4ccc56b..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function b(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},K=u.length,y=[],S=0;Sc)throw new RangeError(d("invalid argument. 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Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index 0f06a47..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From c180a1bbc1df6d39eb42a6a038310b454f4fe086 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Wed, 16 Apr 2025 08:48:59 +0000 Subject: [PATCH 32/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 83 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/index.js | 99 - dist/index.js.map | 7 - 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-# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -227,7 +224,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index d0f0000..0000000 --- a/dist/index.js +++ /dev/null @@ -1,99 +0,0 @@ -"use strict";var fr=function(Y,a){return function(){return a||Y((a={exports:{}}).exports,a),a.exports}};var jv=fr(function(si,Sv){ -function ne(Y,a){var w,r;for(r=2;r0;){for(t0;){for(h0;){for(f0;){for(n0;){for(d0;){for(N0;){for(y0;){for(S0;){for(g0;){for(V0;){for(z0;){for(L0;){for(D0;){for(I0;){for(M0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(P0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(h0;){for(j0;){for(n0;){for(d0;){for(c0;){for(y0;){for(S0;){for(g0;){for(b0;){for(z0;){for(L0;){for(D0;){for(I0;){for(N0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(z0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(F0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A3?m=r:m={},c=a.length,q=[],g=0;gv)throw new RangeError(ev('2AZHn',v,Cr(w,",")));for(n=v-d,g=1;g2?v=J:v={},ei(Y,w,r,v)}}ue.exports=oi -});var fi=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),se=qv(),ui=ie();fi(se,"factory",ui);module.exports=se; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 0c20c14..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 013cb69..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing a subarray of the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..b89ece3 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function b(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},K=u.length,y=[],S=0;Sc)throw new RangeError(d("invalid argument. 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Value: [%s].",c,p(n,",")));for(M=c-L,S=1;S2?f:{};return q(r,s,o,e)}}r(q,"factory",I);export{q as default,I as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..b811d5c --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index aa26161..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index aa0f4c9..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index 3cff64f..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index d06bf95..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 8c8d2f8..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index bf57509..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index ca45081..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index a1ba021..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index efb1480..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index a615dcc..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index e34e82c..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 96bc45f..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 0c56b4b..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 9a7cdd0..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 7882249..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index b6129f5..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index d5781dc..0000000 --- a/lib/main.js +++ /dev/null @@ -1,466 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..e97c7ad --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index 748ff1d..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From d703aae8ff00edc690764e4489ec8f1098b76b8a Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 27 Apr 2025 23:38:32 +0000 Subject: [PATCH 33/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index c7b2bab..248f94b 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 961a9bf..5b2c692 100644 --- a/lib/main.js +++ b/lib/main.js @@ -27,7 +27,7 @@ var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 099fbca..aeae7b7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 20bf9d65ad3b801754bc6e7be24a54223abcbd22 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 27 Apr 2025 23:38:48 +0000 Subject: [PATCH 34/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index b89ece3..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function b(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(nr0;){for(ur0;){for(dr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},K=u.length,y=[],S=0;Sc)throw new RangeError(d("invalid argument. 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Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index e97c7ad..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From e8f07b98b3a52090b4dc2b71c61539b65d5c9058 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Sun, 27 Apr 2025 23:39:10 +0000 Subject: [PATCH 35/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 85 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/index.js | 99 - dist/index.js.map | 7 - 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-# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -227,7 +224,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 10bbeb8..0000000 --- a/dist/index.js +++ /dev/null @@ -1,99 +0,0 @@ -"use strict";var fr=function(Y,a){return function(){return a||Y((a={exports:{}}).exports,a),a.exports}};var jv=fr(function(si,Sv){ -function ne(Y,a){var w,r;for(r=2;r0;){for(t0;){for(h0;){for(f0;){for(n0;){for(d0;){for(N0;){for(y0;){for(S0;){for(g0;){for(V0;){for(z0;){for(L0;){for(D0;){for(I0;){for(M0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(P0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(h0;){for(j0;){for(n0;){for(d0;){for(c0;){for(y0;){for(S0;){for(g0;){for(b0;){for(z0;){for(L0;){for(D0;){for(I0;){for(N0;){for(E0;){for(F0;){for(U0;){for(H0;){for(V0;){for(z0;){for(K0;){for(rr0;){for(vr0;){for(W0;){for(M0;){for(E0;){for(F0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(K0;){for(rr0;){for(vr0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A0;){for(T0;){for(ar0;){for(er0;){for(Z0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(B0;){for(ur0;){for(nr0;){for($0;){for(A3?m=r:m={},c=a.length,q=[],g=0;gv)throw new RangeError(ev('2AZHn',v,Cr(w,",")));for(n=v-d,g=1;g2?v=J:v={},ei(Y,w,r,v)}}ue.exports=oi -});var fi=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),se=qv(),ui=ie();fi(se,"factory",ui);module.exports=se; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index b52c012..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 013cb69..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing a subarray of the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..7cb8fb7 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function y(r,s){var o;for(o=0;o0;){for(k0;){for(P0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(nr0;){for(dr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(k0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(nr0;){for(dr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},L=d.length,A=[],U=0;Uc)throw new RangeError(u("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",c,p(n,",")));for(O=c-M,U=1;U2?f:{};return A(r,s,o,e)}}r(A,"factory",T);export{A as default,T as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..5fde3eb --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index b41cb82..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index b571c18..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index aa26161..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index aa0f4c9..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index 0faf8b9..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index 4e40fea..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index 3cff64f..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index d06bf95..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 8c8d2f8..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index bf57509..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index ca45081..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index a1ba021..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index efb1480..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index a615dcc..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index e34e82c..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 96bc45f..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 0c56b4b..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 9a7cdd0..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 7882249..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index b6129f5..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var isRowMajor = require( '@stdlib/ndarray-base-assert-is-row-major-string' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor( y.order ) ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 248f94b..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 5b2c692..0000000 --- a/lib/main.js +++ /dev/null @@ -1,466 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - if ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) { - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index aeae7b7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-assert-is-row-major-string": "github:stdlib-js/ndarray-base-assert-is-row-major-string#main", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..de2d8aa --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index 748ff1d..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 38b174b883f17527c8505a252f345d5476cf5f2f Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 20 May 2025 07:48:28 +0000 Subject: [PATCH 36/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index 7d3848a..99cb1ac 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 5bfdc85..80bbe42 100644 --- a/lib/main.js +++ b/lib/main.js @@ -28,7 +28,7 @@ var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var strides2order = require( '@stdlib/ndarray-base-strides2order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 4b3f646..5a46cf7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 8a744dcdd9318c1dc6a07a2e21a2f98857d9fd1a Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 20 May 2025 07:48:48 +0000 Subject: [PATCH 37/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 7cb8fb7..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-assert-is-row-major-string@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function y(r,s){var o;for(o=0;o0;){for(k0;){for(P0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(nr0;){for(dr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(k0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(nr0;){for(dr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?i:{},L=d.length,A=[],U=0;Uc)throw new RangeError(u("invalid argument. 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Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tif ( iox !== 0 && ioy !== 0 && iox === ioy && K <= MAX_DIMS ) {\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport isRowMajor from '@stdlib/ndarray-base-assert-is-row-major-string';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor( y.order ) ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Return a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index de2d8aa..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From f7736a400c21c969a76e448ee0e71e26d3be1da7 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 20 May 2025 07:49:14 +0000 Subject: [PATCH 38/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 93 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/index.js | 99 - dist/index.js.map | 7 - 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-# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -227,7 +224,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index 85eaa96..0000000 --- a/dist/index.js +++ /dev/null @@ -1,99 +0,0 @@ -"use strict";var fr=function(U,a){return function(){return a||U((a={exports:{}}).exports,a),a.exports}};var xv=fr(function(Lu,Sv){ -function he(U,a){var I,r;for(r=2;r0;){for(p0;){for(l0;){for(o0;){for(n0;){for(c0;){for(V0;){for(h0;){for(S0;){for(m0;){for(z0;){for(N0;){for(K0;){for(P0;){for(w0;){for(A0;){for(E0;){for(Y0;){for(L0;){for(G0;){for(z0;){for(_0;){for(T0;){for(vr0;){for($0;){for(W0;){for(A0;){for(E0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(T0;){for(vr0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(M0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(l0;){for(e0;){for(n0;){for(c0;){for(q0;){for(h0;){for(S0;){for(m0;){for(j0;){for(N0;){for(K0;){for(P0;){for(w0;){for(V0;){for(E0;){for(Y0;){for(L0;){for(G0;){for(z0;){for(N0;){for(T0;){for(vr0;){for($0;){for(W0;){for(A0;){for(E0;){for(Y0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(T0;){for(vr0;){for($0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R3?y=r:y={},c=a.length,x=[],S=0;Sv)throw new RangeError(ev('2AZHn',v,Pr(I,",")));for(o=v-n,S=1;S2?v=J:v={},Yu(U,I,r,v)}}ie.exports=Ku -});var Tu=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),ne=qv(),Bu=se();Tu(ne,"factory",Bu);module.exports=ne; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index a34c67c..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar strides2order = require( '@stdlib/ndarray-base-strides2order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunary10d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "ord", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 013cb69..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing a subarray of the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..fdd5b79 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function b(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},M=d.length,y=[],W=0;Wm)throw new RangeError(n("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",m,u(i,",")));for(Q=m-O,W=1;W2?f:{};return q(r,s,o,e)}}r(q,"factory",I);export{q as default,I as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..93a385a --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index 90f58ee..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index dd7234c..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index 428591c..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index 113b26b..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv8.push( sv[8] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index dade268..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index bc3026d..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index a8f6c6e..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index 44fc164..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 63d7e9e..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index c212572..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index 9c7e7aa..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index fe9a796..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index a296861..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index cafbe6e..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index 87df811..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 468524a..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 35ec78a..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 8d18558..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 14509e8..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index 355ed51..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 99cb1ac..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 80bbe42..0000000 --- a/lib/main.js +++ /dev/null @@ -1,469 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var strides2order = require( '@stdlib/ndarray-base-strides2order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var ord; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - ord = strides2order( sl ); - if ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index 5a46cf7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-strides2order": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..0d5cbb7 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index 748ff1d..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 404104070aebcf99bfacfce98c05eab800c07f60 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 20 May 2025 07:50:12 +0000 Subject: [PATCH 39/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index 7d3848a..99cb1ac 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 5bfdc85..80bbe42 100644 --- a/lib/main.js +++ b/lib/main.js @@ -28,7 +28,7 @@ var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var strides2order = require( '@stdlib/ndarray-base-strides2order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 4b3f646..5a46cf7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 33079262785296c3fd16e6d017432b9b58029c79 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 20 May 2025 07:50:33 +0000 Subject: [PATCH 40/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index fdd5b79..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function b(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},M=d.length,y=[],W=0;Wm)throw new RangeError(n("invalid argument. 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obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv8.push( sv[8] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index 0d5cbb7..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From 008215972e305d8d11c0b40e49912418d3452ae6 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 20 May 2025 07:50:58 +0000 Subject: [PATCH 41/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 95 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/index.js | 99 - dist/index.js.map | 7 - 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-# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -227,7 +224,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index b76ffd5..0000000 --- a/dist/index.js +++ /dev/null @@ -1,99 +0,0 @@ -"use strict";var fr=function(U,a){return function(){return a||U((a={exports:{}}).exports,a),a.exports}};var xv=fr(function(Lu,Sv){ -function he(U,a){var I,r;for(r=2;r0;){for(p0;){for(l0;){for(f0;){for(s0;){for(c0;){for(V0;){for(h0;){for(S0;){for(m0;){for(z0;){for(N0;){for(K0;){for(P0;){for(w0;){for(A0;){for(E0;){for(Y0;){for(L0;){for(G0;){for(z0;){for(_0;){for(T0;){for(vr0;){for($0;){for(W0;){for(A0;){for(E0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(T0;){for(vr0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(M0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(l0;){for(o0;){for(s0;){for(c0;){for(q0;){for(h0;){for(S0;){for(m0;){for(j0;){for(N0;){for(K0;){for(P0;){for(w0;){for(V0;){for(E0;){for(Y0;){for(L0;){for(G0;){for(z0;){for(N0;){for(T0;){for(vr0;){for($0;){for(W0;){for(A0;){for(E0;){for(Y0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(T0;){for(vr0;){for($0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R3?y=r:y={},c=a.length,x=[],S=0;Sv)throw new RangeError(ev('2AZHn',v,Pr(I,",")));for(f=v-s,S=1;S2?v=J:v={},Yu(U,I,r,v)}}ie.exports=Ku -});var Tu=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),ne=qv(),Bu=se();Tu(ne,"factory",Bu);module.exports=ne; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index d286dc9..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar strides2order = require( '@stdlib/ndarray-base-strides2order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunary10d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "ord", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index 013cb69..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing a subarray of the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..d445ad7 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function v(r,s){var o;for(o=0;o0;){for(k0;){for(P0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(k0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},M=d.length,A=[],W=0;Wm)throw new RangeError(n("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",m,u(i,",")));for(Q=m-O,W=1;W2?f:{};return z(r,s,o,e)}}r(z,"factory",A);export{z as default,A as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..630d59b --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index 90f58ee..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index dd7234c..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index fa92d91..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index 3f60306..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index dade268..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index bc3026d..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index a8f6c6e..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index 44fc164..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 63d7e9e..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index c212572..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index 9c7e7aa..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index fe9a796..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index a296861..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index cafbe6e..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index 87df811..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 468524a..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 35ec78a..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 8d18558..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 14509e8..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index 355ed51..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 99cb1ac..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 80bbe42..0000000 --- a/lib/main.js +++ /dev/null @@ -1,469 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var strides2order = require( '@stdlib/ndarray-base-strides2order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var ord; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - ord = strides2order( sl ); - if ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index 5a46cf7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-strides2order": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..a11bbc7 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index 748ff1d..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From ae476b7c7cd8b3683a0870d82dd70c328f473ce7 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 24 Jun 2025 08:30:53 +0000 Subject: [PATCH 42/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index 7d3848a..99cb1ac 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 5bfdc85..80bbe42 100644 --- a/lib/main.js +++ b/lib/main.js @@ -28,7 +28,7 @@ var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var strides2order = require( '@stdlib/ndarray-base-strides2order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 4b3f646..5a46cf7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 0bc31afeb4edd542e2f7f7bd39fa55634c8cb04e Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 24 Jun 2025 08:31:28 +0000 Subject: [PATCH 43/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index d445ad7..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function v(r,s){var o;for(o=0;o0;){for(k0;){for(P0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(k0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},M=d.length,A=[],W=0;Wm)throw new RangeError(n("invalid argument. 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obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index a11bbc7..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From 05775275caeb011bc3178dd123756c03ecac885a Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Tue, 24 Jun 2025 08:31:53 +0000 Subject: [PATCH 44/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 96 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/0d.js | 92 - 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--git a/.editorconfig b/.editorconfig deleted file mode 100644 index dab5d2a..0000000 --- a/.editorconfig +++ /dev/null @@ -1,180 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -227,7 +224,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/0d.js b/dist/0d.js deleted file mode 100644 index 90f58ee..0000000 --- a/dist/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/dist/0d_accessors.js b/dist/0d_accessors.js deleted file mode 100644 index dd7234c..0000000 --- a/dist/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/dist/10d.js b/dist/10d.js deleted file mode 100644 index fa92d91..0000000 --- a/dist/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/dist/10d_accessors.js b/dist/10d_accessors.js deleted file mode 100644 index 3f60306..0000000 --- a/dist/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/dist/10d_blocked.js b/dist/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/dist/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/dist/10d_blocked_accessors.js b/dist/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/dist/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/dist/1d.js b/dist/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/dist/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/dist/1d_accessors.js b/dist/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/dist/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/dist/2d.js b/dist/2d.js deleted file mode 100644 index dade268..0000000 --- a/dist/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/dist/2d_accessors.js b/dist/2d_accessors.js deleted file mode 100644 index bc3026d..0000000 --- a/dist/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/dist/2d_blocked.js b/dist/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/dist/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/dist/2d_blocked_accessors.js b/dist/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/dist/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/dist/3d.js b/dist/3d.js deleted file mode 100644 index a8f6c6e..0000000 --- a/dist/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/dist/3d_accessors.js b/dist/3d_accessors.js deleted file mode 100644 index 44fc164..0000000 --- a/dist/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/dist/3d_blocked.js b/dist/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/dist/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/dist/3d_blocked_accessors.js b/dist/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/dist/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/dist/4d.js b/dist/4d.js deleted file mode 100644 index 63d7e9e..0000000 --- a/dist/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/dist/4d_accessors.js b/dist/4d_accessors.js deleted file mode 100644 index c212572..0000000 --- a/dist/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/dist/4d_blocked.js b/dist/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/dist/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/dist/4d_blocked_accessors.js b/dist/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/dist/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/dist/5d.js b/dist/5d.js deleted file mode 100644 index 9c7e7aa..0000000 --- a/dist/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/dist/5d_accessors.js b/dist/5d_accessors.js deleted file mode 100644 index fe9a796..0000000 --- a/dist/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/dist/5d_blocked.js b/dist/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/dist/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/dist/5d_blocked_accessors.js b/dist/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/dist/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/dist/6d.js b/dist/6d.js deleted file mode 100644 index a296861..0000000 --- a/dist/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/dist/6d_accessors.js b/dist/6d_accessors.js deleted file mode 100644 index cafbe6e..0000000 --- a/dist/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/dist/6d_blocked.js b/dist/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/dist/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/dist/6d_blocked_accessors.js b/dist/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/dist/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/dist/7d.js b/dist/7d.js deleted file mode 100644 index 87df811..0000000 --- a/dist/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/dist/7d_accessors.js b/dist/7d_accessors.js deleted file mode 100644 index 468524a..0000000 --- a/dist/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/dist/7d_blocked.js b/dist/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/dist/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/dist/7d_blocked_accessors.js b/dist/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/dist/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/dist/8d.js b/dist/8d.js deleted file mode 100644 index 35ec78a..0000000 --- a/dist/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/dist/8d_accessors.js b/dist/8d_accessors.js deleted file mode 100644 index 8d18558..0000000 --- a/dist/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/dist/8d_blocked.js b/dist/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/dist/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/dist/8d_blocked_accessors.js b/dist/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/dist/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/dist/9d.js b/dist/9d.js deleted file mode 100644 index 14509e8..0000000 --- a/dist/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/dist/9d_accessors.js b/dist/9d_accessors.js deleted file mode 100644 index 355ed51..0000000 --- a/dist/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/dist/9d_blocked.js b/dist/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/dist/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/dist/9d_blocked_accessors.js b/dist/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/dist/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/dist/factory.js b/dist/factory.js deleted file mode 100644 index 7d3848a..0000000 --- a/dist/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/dist/increment_offsets.js b/dist/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/dist/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index bc40bcf..0000000 --- a/dist/index.js +++ /dev/null @@ -1,129 +0,0 @@ -/** @license Apache-2.0 */ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property/dist' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index d286dc9..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar strides2order = require( '@stdlib/ndarray-base-strides2order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunary10d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "ord", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/dist/initialize_array_views.js b/dist/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/dist/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/dist/main.js b/dist/main.js deleted file mode 100644 index 5bfdc85..0000000 --- a/dist/main.js +++ /dev/null @@ -1,469 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var strides2order = require( '@stdlib/ndarray-base-strides2order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var ord; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - ord = strides2order( sl ); - if ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/dist/nd.js b/dist/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/dist/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/dist/nd_accessors.js b/dist/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/dist/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/dist/offsets.js b/dist/offsets.js deleted file mode 100644 index a606628..0000000 --- a/dist/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/dist/set_view_offsets.js b/dist/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/dist/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index c2b8b99..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing a subarray of the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > var x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > var y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..ac80f29 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import b from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function w(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(ur0;){for(nr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(nr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(ur0;){for(nr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},Q=d.length,b=[],Y=0;Ym)throw new RangeError(u("invalid argument. 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Value: [%s].",m,n(i,",")));for(U=m-S,Y=1;Y2?f:{};return I(r,s,o,e)}}r(I,"factory",R);export{I as default,R as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..308ed65 --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index 90f58ee..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index dd7234c..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index fa92d91..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index 3f60306..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index dade268..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index bc3026d..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index a8f6c6e..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index 44fc164..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 63d7e9e..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index c212572..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index 9c7e7aa..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index fe9a796..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index a296861..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index cafbe6e..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index 87df811..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 468524a..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 35ec78a..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 8d18558..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 14509e8..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index 355ed51..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 99cb1ac..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 80bbe42..0000000 --- a/lib/main.js +++ /dev/null @@ -1,469 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var strides2order = require( '@stdlib/ndarray-base-strides2order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var ord; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - ord = strides2order( sl ); - if ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index 5a46cf7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-strides2order": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..0d60269 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index 748ff1d..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From 923fa0205994ac12d8cb368b1c618ffc12e62349 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Mon, 11 Aug 2025 01:23:59 +0000 Subject: [PATCH 45/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index 7d3848a..99cb1ac 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 5bfdc85..80bbe42 100644 --- a/lib/main.js +++ b/lib/main.js @@ -28,7 +28,7 @@ var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var strides2order = require( '@stdlib/ndarray-base-strides2order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 4b3f646..5a46cf7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 2dfaf3ebdeedc8a7be63159874d96980248765b6 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Mon, 11 Aug 2025 01:38:16 +0000 Subject: [PATCH 46/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index ac80f29..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs";import y from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import j from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import x from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import b from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function w(r,s){var o;for(o=0;o0;){for(P0;){for(N0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(ur0;){for(nr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(P0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(nr0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(ur0;){for(nr0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},Q=d.length,b=[],Y=0;Ym)throw new RangeError(u("invalid argument. 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obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index 0d60269..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From c53c1786bf34b36d02d103f1fb2b7d2f45354b69 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Mon, 11 Aug 2025 01:38:44 +0000 Subject: [PATCH 47/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/.keepalive | 1 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 96 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/index.js | 99 - 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-# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/.keepalive b/.github/.keepalive deleted file mode 100644 index 6969dde..0000000 --- a/.github/.keepalive +++ /dev/null @@ -1 +0,0 @@ -2025-08-11T01:16:37.114Z diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -227,7 +224,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index b76ffd5..0000000 --- a/dist/index.js +++ /dev/null @@ -1,99 +0,0 @@ -"use strict";var fr=function(U,a){return function(){return a||U((a={exports:{}}).exports,a),a.exports}};var xv=fr(function(Lu,Sv){ -function he(U,a){var I,r;for(r=2;r0;){for(p0;){for(l0;){for(f0;){for(s0;){for(c0;){for(V0;){for(h0;){for(S0;){for(m0;){for(z0;){for(N0;){for(K0;){for(P0;){for(w0;){for(A0;){for(E0;){for(Y0;){for(L0;){for(G0;){for(z0;){for(_0;){for(T0;){for(vr0;){for($0;){for(W0;){for(A0;){for(E0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(T0;){for(vr0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(M0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(l0;){for(o0;){for(s0;){for(c0;){for(q0;){for(h0;){for(S0;){for(m0;){for(j0;){for(N0;){for(K0;){for(P0;){for(w0;){for(V0;){for(E0;){for(Y0;){for(L0;){for(G0;){for(z0;){for(N0;){for(T0;){for(vr0;){for($0;){for(W0;){for(A0;){for(E0;){for(Y0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(_0;){for(T0;){for(vr0;){for($0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R0;){for(B0;){for(ar0;){for(er0;){for(Z0;){for(X0;){for(tr0;){for(cr0;){for(or0;){for(C0;){for(F0;){for(ur0;){for(nr0;){for(rr0;){for(R3?y=r:y={},c=a.length,x=[],S=0;Sv)throw new RangeError(ev('2AZHn',v,Pr(I,",")));for(f=v-s,S=1;S2?v=J:v={},Yu(U,I,r,v)}}ie.exports=Ku -});var Tu=require('@stdlib/utils-define-nonenumerable-read-only-property/dist'),ne=qv(),Bu=se();Tu(ne,"factory",Bu);module.exports=ne; -/** @license Apache-2.0 */ -//# sourceMappingURL=index.js.map diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index d286dc9..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar strides2order = require( '@stdlib/ndarray-base-strides2order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunary10d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "ord", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index c2b8b99..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing a subarray of the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > var x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > var y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..02df438 --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function y(r,s){var o;for(o=0;o0;){for(k0;){for(P0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(k0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},M=d.length,A=[],W=0;Wm)throw new RangeError(n("invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].",m,u(i,",")));for(Q=m-O,W=1;W2?f:{};return A(r,s,o,e)}}r(A,"factory",T);export{A as default,T as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..eaf86eb --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index 90f58ee..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index dd7234c..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index fa92d91..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index 3f60306..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index d874e0f..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 715c7e5..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9 = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index dade268..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index bc3026d..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index a8f6c6e..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index 44fc164..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 63d7e9e..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index c212572..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index 9c7e7aa..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index fe9a796..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index a296861..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index cafbe6e..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index dd0372c..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 3492757..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index 87df811..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 468524a..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 3f941b8..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index 440b938..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 35ec78a..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 8d18558..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index 9735405..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index 41ea0ad..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 14509e8..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index 355ed51..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index 022c7da..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 05c12c5..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8 = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7 = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6 = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5 = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 99cb1ac..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 80bbe42..0000000 --- a/lib/main.js +++ /dev/null @@ -1,469 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var strides2order = require( '@stdlib/ndarray-base-strides2order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var ord; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - ord = strides2order( sl ); - if ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index 5a46cf7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-strides2order": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..9f49b4f --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index 748ff1d..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests From f4e06fa33ab8b0d572aca8ffa448b4aa642e113f Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Fri, 15 Aug 2025 21:06:21 +0000 Subject: [PATCH 48/50] Transform error messages --- lib/factory.js | 4 ++-- lib/main.js | 2 +- package.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/factory.js b/lib/factory.js index 7d3848a..99cb1ac 100644 --- a/lib/factory.js +++ b/lib/factory.js @@ -21,7 +21,7 @@ // MODULES // var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var reduce = require( './main.js' ); @@ -88,7 +88,7 @@ var reduce = require( './main.js' ); */ function factory( fcn ) { if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); + throw new TypeError( format( 'null3c', fcn ) ); } return reducer; diff --git a/lib/main.js b/lib/main.js index 5bfdc85..80bbe42 100644 --- a/lib/main.js +++ b/lib/main.js @@ -28,7 +28,7 @@ var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); var strides2order = require( '@stdlib/ndarray-base-strides2order' ); var numel = require( '@stdlib/ndarray-base-numel' ); var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); +var format = require( '@stdlib/error-tools-fmtprodmsg' ); var initializeViews = require( './initialize_array_views.js' ); var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); diff --git a/package.json b/package.json index 4b3f646..5a46cf7 100644 --- a/package.json +++ b/package.json @@ -50,7 +50,7 @@ "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/string-format": "^0.2.2", + "@stdlib/error-tools-fmtprodmsg": "^0.2.2", "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", "@stdlib/error-tools-fmtprodmsg": "^0.2.2" }, From 1897b4e513eff3c87ba78e05b17d34daaf2c7e36 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Fri, 15 Aug 2025 21:06:40 +0000 Subject: [PATCH 49/50] Remove files --- index.mjs | 4 - index.mjs.map | 1 - stats.html | 4842 ------------------------------------------------- 3 files changed, 4847 deletions(-) delete mode 100644 index.mjs delete mode 100644 index.mjs.map delete mode 100644 stats.html diff --git a/index.mjs b/index.mjs deleted file mode 100644 index 02df438..0000000 --- a/index.mjs +++ /dev/null @@ -1,4 +0,0 @@ -// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 -/// -import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function y(r,s){var o;for(o=0;o0;){for(k0;){for(P0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(k0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},M=d.length,A=[],W=0;Wm)throw new RangeError(n("invalid argument. 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Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9 = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8 = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7 = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6 = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5 = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/stats.html b/stats.html deleted file mode 100644 index 9f49b4f..0000000 --- a/stats.html +++ /dev/null @@ -1,4842 +0,0 @@ - - - - - - - - Rollup Visualizer - - - -
- - - - - From 98dc11d52b3030c856c2226d1292cb73821f7979 Mon Sep 17 00:00:00 2001 From: stdlib-bot Date: Fri, 15 Aug 2025 21:07:02 +0000 Subject: [PATCH 50/50] Auto-generated commit --- .editorconfig | 180 - .eslintrc.js | 1 - .gitattributes | 66 - .github/PULL_REQUEST_TEMPLATE.md | 7 - .github/workflows/cancel.yml | 57 - .github/workflows/close_pull_requests.yml | 54 - .github/workflows/examples.yml | 64 - .github/workflows/npm_downloads.yml | 112 - .github/workflows/productionize.yml | 794 --- .github/workflows/publish.yml | 252 - .github/workflows/test.yml | 99 - .github/workflows/test_bundles.yml | 186 - .github/workflows/test_coverage.yml | 133 - .github/workflows/test_install.yml | 85 - .github/workflows/test_published_package.yml | 105 - .gitignore | 194 - .npmignore | 229 - .npmrc | 31 - CHANGELOG.md | 98 - CITATION.cff | 30 - CODE_OF_CONDUCT.md | 3 - CONTRIBUTING.md | 3 - Makefile | 534 -- README.md | 57 +- SECURITY.md | 5 - branches.md | 56 - dist/0d.js | 92 - 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--git a/.editorconfig b/.editorconfig deleted file mode 100644 index dab5d2a..0000000 --- a/.editorconfig +++ /dev/null @@ -1,180 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# EditorConfig configuration file (see ). - -# Indicate that this file is a root-level configuration file: -root = true - -# Set properties for all files: -[*] -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true - -# Set properties for JavaScript files: -[*.{js,js.txt}] -indent_style = tab - -# Set properties for JavaScript ES module files: -[*.{mjs,mjs.txt}] -indent_style = tab - -# Set properties for JavaScript CommonJS files: -[*.{cjs,cjs.txt}] -indent_style = tab - -# Set properties for JSON files: -[*.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `cli_opts.json` files: -[cli_opts.json] -indent_style = tab - -# Set properties for TypeScript files: -[*.ts] -indent_style = tab - -# Set properties for Python files: -[*.{py,py.txt}] -indent_style = space -indent_size = 4 - -# Set properties for Julia files: -[*.{jl,jl.txt}] -indent_style = tab - -# Set properties for R files: -[*.{R,R.txt}] -indent_style = tab - -# Set properties for C files: -[*.{c,c.txt}] -indent_style = tab - -# Set properties for C header files: -[*.{h,h.txt}] -indent_style = tab - -# Set properties for C++ files: -[*.{cpp,cpp.txt}] -indent_style = tab - -# Set properties for C++ header files: -[*.{hpp,hpp.txt}] -indent_style = tab - -# Set properties for Fortran files: -[*.{f,f.txt}] -indent_style = space -indent_size = 2 - -# Set properties for shell files: -[*.{sh,sh.txt}] -indent_style = tab - -# Set properties for AWK files: -[*.{awk,awk.txt}] -indent_style = tab - -# Set properties for HTML files: -[*.{html,html.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for XML files: -[*.{xml,xml.txt}] -indent_style = tab -tab_width = 2 - -# Set properties for CSS files: -[*.{css,css.txt}] -indent_style = tab - -# Set properties for Makefiles: -[Makefile] -indent_style = tab - -[*.{mk,mk.txt}] -indent_style = tab - -# Set properties for Markdown files: -[*.{md,md.txt}] -indent_style = space -indent_size = 4 -trim_trailing_whitespace = true # Note: this disables using two spaces to force a hard line break, which is permitted in Markdown. As we don't typically follow that practice (TMK), we should be safe to automatically trim. - -# Set properties for `usage.txt` files: -[usage.txt] -indent_style = space -indent_size = 2 - -# Set properties for `repl.txt` files: -[repl.txt] -indent_style = space -indent_size = 4 - -# Set properties for `package.json` files: -[package.{json,json.txt}] -indent_style = space -indent_size = 2 - -# Set properties for `datapackage.json` files: -[datapackage.json] -indent_style = space -indent_size = 2 - -# Set properties for `manifest.json` files: -[manifest.json] -indent_style = space -indent_size = 2 - -# Set properties for `tsconfig.json` files: -[tsconfig.json] -indent_style = space -indent_size = 2 - -# Set properties for LaTeX files: -[*.{tex,tex.txt}] -indent_style = tab - -# Set properties for LaTeX Bibliography files: -[*.{bib,bib.txt}] -indent_style = tab - -# Set properties for YAML files: -[*.{yml,yml.txt}] -indent_style = space -indent_size = 2 - -# Set properties for GYP files: -[binding.gyp] -indent_style = space -indent_size = 2 - -[*.gypi] -indent_style = space -indent_size = 2 - -# Set properties for citation files: -[*.{cff,cff.txt}] -indent_style = space -indent_size = 2 diff --git a/.eslintrc.js b/.eslintrc.js deleted file mode 100644 index 5f30286..0000000 --- a/.eslintrc.js +++ /dev/null @@ -1 +0,0 @@ -/* For the `eslint` rules of this project, consult the main repository at https://github.com/stdlib-js/stdlib */ diff --git a/.gitattributes b/.gitattributes deleted file mode 100644 index 1c88e69..0000000 --- a/.gitattributes +++ /dev/null @@ -1,66 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2017 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Configuration file which assigns attributes to pathnames. -# -# [1]: https://git-scm.com/docs/gitattributes - -# Automatically normalize the line endings of any committed text files: -* text=auto - -# Override line endings for certain files on checkout: -*.crlf.csv text eol=crlf - -# Denote that certain files are binary and should not be modified: -*.png binary -*.jpg binary -*.jpeg binary -*.gif binary -*.ico binary -*.gz binary -*.zip binary -*.7z binary -*.mp3 binary -*.mp4 binary -*.mov binary - -# Override what is considered "vendored" by GitHub's linguist: -/lib/node_modules/** -linguist-vendored -linguist-generated - -# Configure directories which should *not* be included in GitHub language statistics: -/deps/** linguist-vendored -/dist/** linguist-generated -/workshops/** linguist-vendored - -benchmark/** linguist-vendored -docs/* linguist-documentation -etc/** linguist-vendored -examples/** linguist-documentation -scripts/** linguist-vendored -test/** linguist-vendored -tools/** linguist-vendored - -# Configure files which should *not* be included in GitHub language statistics: -Makefile linguist-vendored -*.mk linguist-vendored -*.jl linguist-vendored -*.py linguist-vendored -*.R linguist-vendored - -# Configure files which should be included in GitHub language statistics: -docs/types/*.d.ts -linguist-documentation diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md deleted file mode 100644 index 0fa999a..0000000 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ /dev/null @@ -1,7 +0,0 @@ - - -We are excited about your pull request, but unfortunately we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. - -If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. You may also consult the [development guide](https://github.com/stdlib-js/stdlib/blob/develop/docs/contributing/development.md) for help on developing stdlib. - -We look forward to receiving your contribution! :smiley: \ No newline at end of file diff --git a/.github/workflows/cancel.yml b/.github/workflows/cancel.yml deleted file mode 100644 index b5291db..0000000 --- a/.github/workflows/cancel.yml +++ /dev/null @@ -1,57 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: cancel - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to cancel existing workflow runs: - cancel: - - # Define a display name: - name: 'Cancel workflow runs' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Time limit: - timeout-minutes: 3 - - # Define the sequence of job steps... - steps: - - # Cancel existing workflow runs: - - name: 'Cancel existing workflow runs' - # Pin action to full length commit SHA - uses: styfle/cancel-workflow-action@85880fa0301c86cca9da44039ee3bb12d3bedbfa # v0.12.1 - with: - workflow_id: >- - benchmark.yml, - examples.yml, - test.yml, - test_coverage.yml, - test_install.yml, - publish.yml - access_token: ${{ github.token }} diff --git a/.github/workflows/close_pull_requests.yml b/.github/workflows/close_pull_requests.yml deleted file mode 100644 index a04ae7d..0000000 --- a/.github/workflows/close_pull_requests.yml +++ /dev/null @@ -1,54 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: close_pull_requests - -# Workflow triggers: -on: - pull_request_target: - types: [opened] - -# Workflow jobs: -jobs: - - # Define job to close all pull requests: - run: - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Close pull request - - name: 'Close pull request' - # Pin action to full length commit SHA corresponding to v3.1.2 - uses: superbrothers/close-pull-request@9c18513d320d7b2c7185fb93396d0c664d5d8448 - with: - comment: | - Thank you for submitting a pull request. :raised_hands: - - We greatly appreciate your willingness to submit a contribution. However, we are not accepting pull requests against this repository, as all development happens on the [main project repository](https://github.com/stdlib-js/stdlib). - - We kindly request that you submit this pull request against the [respective directory](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray) of the main repository where we’ll review and provide feedback. If this is your first stdlib contribution, be sure to read the [contributing guide](https://github.com/stdlib-js/stdlib/blob/develop/CONTRIBUTING.md) which provides guidelines and instructions for submitting contributions. - - Thank you again, and we look forward to receiving your contribution! :smiley: - - Best, - The stdlib team \ No newline at end of file diff --git a/.github/workflows/examples.yml b/.github/workflows/examples.yml deleted file mode 100644 index 2984901..0000000 --- a/.github/workflows/examples.yml +++ /dev/null @@ -1,64 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2021 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: examples - -# Workflow triggers: -on: - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job to run the package examples... - examples: - - # Define display name: - name: 'Run examples' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - - # Checkout repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Run examples: - - name: 'Run examples' - run: | - npm run examples diff --git a/.github/workflows/npm_downloads.yml b/.github/workflows/npm_downloads.yml deleted file mode 100644 index fdebb7c..0000000 --- a/.github/workflows/npm_downloads.yml +++ /dev/null @@ -1,112 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: npm_downloads - -# Workflow triggers: -on: - # Run this workflow weekly: - schedule: - # cron: ' ' - - cron: '23 11 * * 4' - - # Allow the workflow to be manually run: - workflow_dispatch: - -# Workflow jobs: -jobs: - - # Define a job for retrieving npm download counts... - npm_downloads: - - # Define display name: - name: 'Retrieve npm download counts' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - timeout-minutes: 10 - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Resolve package name: - - name: 'Resolve package name' - id: package_name - run: | - name=`node -e 'console.log(require("./package.json").name)' | tr -d '\n'` - echo "package_name=$name" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Fetch download data: - - name: 'Fetch data' - id: download_data - run: | - url="https://api.npmjs.org/downloads/range/$(date --date='1 year ago' '+%Y-%m-%d'):$(date '+%Y-%m-%d')/${{ steps.package_name.outputs.package_name }}" - echo "$url" - data=$(curl "$url") - mkdir ./tmp - echo "$data" > ./tmp/npm_downloads.json - echo "data=$data" >> $GITHUB_OUTPUT - timeout-minutes: 5 - - # Print summary of download data: - - name: 'Print summary' - run: | - echo "| Date | Downloads |" >> $GITHUB_STEP_SUMMARY - echo "|------|------------|" >> $GITHUB_STEP_SUMMARY - cat ./tmp/npm_downloads.json | jq -r ".downloads | .[-14:] | to_entries | map(\"| \(.value.day) | \(.value.downloads) |\") |.[]" >> $GITHUB_STEP_SUMMARY - - # Upload the download data: - - name: 'Upload data' - # Pin action to full length commit SHA - uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1 - with: - # Define a name for the uploaded artifact (ensuring a unique name for each job): - name: npm_downloads - - # Specify the path to the file to upload: - path: ./tmp/npm_downloads.json - - # Specify the number of days to retain the artifact (default is 90 days): - retention-days: 90 - timeout-minutes: 10 - if: success() - - # Send data to events server: - - name: 'Post data' - # Pin action to full length commit SHA - uses: distributhor/workflow-webhook@48a40b380ce4593b6a6676528cd005986ae56629 # v3.0.3 - env: - webhook_url: ${{ secrets.STDLIB_NPM_DOWNLOADS_URL }} - webhook_secret: ${{ secrets.STDLIB_WEBHOOK_SECRET }} - data: '{ "downloads": ${{ steps.download_data.outputs.data }} }' - timeout-minutes: 5 - if: success() diff --git a/.github/workflows/productionize.yml b/.github/workflows/productionize.yml deleted file mode 100644 index f4575e9..0000000 --- a/.github/workflows/productionize.yml +++ /dev/null @@ -1,794 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2022 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# Workflow name: -name: productionize - -# Workflow triggers: -on: - # Run workflow when a new commit is pushed to the main branch: - push: - branches: - - main - - # Allow the workflow to be manually run: - workflow_dispatch: - inputs: - require-passing-tests: - description: 'Require passing tests for creating bundles' - type: boolean - default: true - - # Run workflow upon completion of `publish` workflow run: - workflow_run: - workflows: ["publish"] - types: [completed] - - -# Concurrency group to prevent multiple concurrent executions: -concurrency: - group: productionize - cancel-in-progress: true - -# Workflow jobs: -jobs: - - # Define a job to create a production build... - productionize: - - # Define display name: - name: 'Productionize' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Define the sequence of job steps... - steps: - # Checkout main branch of repository: - - name: 'Checkout main branch' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - ref: main - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Create production branch: - - name: 'Create production branch' - run: | - git checkout -b production - - # Transform error messages: - - name: 'Transform error messages' - id: transform-error-messages - uses: stdlib-js/transform-errors-action@main - - # Change `@stdlib/string-format` to `@stdlib/error-tools-fmtprodmsg` in package.json if the former is a dependency, otherwise insert it as a dependency: - - name: 'Update dependencies in package.json' - run: | - PKG_VERSION=$(npm view @stdlib/error-tools-fmtprodmsg version) - if grep -q '"@stdlib/string-format"' package.json; then - sed -i "s/\"@stdlib\/string-format\": \"^.*\"/\"@stdlib\/error-tools-fmtprodmsg\": \"^$PKG_VERSION\"/g" package.json - else - node -e "var pkg = require( './package.json' ); pkg.dependencies[ '@stdlib/error-tools-fmtprodmsg' ] = '^$PKG_VERSION'; require( 'fs' ).writeFileSync( 'package.json', JSON.stringify( pkg, null, 2 ) );" - fi - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Transform error messages" - - # Push changes: - - name: 'Push changes' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" production --force - - # Define a job for running tests of the productionized code... - test: - - # Define a display name: - name: 'Run Tests' - - # Define the type of virtual host machine: - runs-on: 'ubuntu-latest' - - # Indicate that this job depends on the prior job finishing: - needs: productionize - - # Run this job regardless of the outcome of the prior job: - if: always() - - # Define the sequence of job steps... - steps: - - # Checkout the repository: - - name: 'Checkout repository' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - with: - # Use the `production` branch: - ref: production - - # Install Node.js: - - name: 'Install Node.js' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Build native add-on if present: - - name: 'Build native add-on (if present)' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - run: | - if [ -f "binding.gyp" ]; then - npm install node-gyp --no-save && ./node_modules/.bin/node-gyp rebuild - fi - - # Run tests: - - name: 'Run tests' - if: ${{ github.event.inputs.require-passing-tests == 'true' }} - id: tests - run: | - npm test || npm test || npm test - - # Define job to create a bundle for use in Deno... - deno: - - # Define display name: - name: 'Create Deno bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `deno` branch exists: - - name: 'Check if remote `deno` branch exists' - id: deno-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin deno - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `deno` exists, delete everything in branch and merge `production` into it - - name: 'If `deno` exists, delete everything in branch and merge `production` into it' - if: steps.deno-branch-exists.outputs.remote-exists - run: | - git checkout -b deno origin/deno - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `deno` does not exist, create `deno` branch: - - name: 'If `deno` does not exist, create `deno` branch' - if: ${{ steps.deno-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b deno - - # Copy files to deno directory: - - name: 'Copy files to deno directory' - run: | - mkdir -p deno - cp README.md LICENSE CONTRIBUTORS NOTICE ./deno - - # Copy TypeScript definitions to deno directory: - if [ -d index.d.ts ]; then - cp index.d.ts ./deno/index.d.ts - fi - if [ -e ./docs/types/index.d.ts ]; then - cp ./docs/types/index.d.ts ./deno/mod.d.ts - fi - - # Install Node.js: - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: Install production and development dependencies - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Bundle package for use in Deno: - - name: 'Bundle package for Deno' - id: deno-bundle - uses: stdlib-js/bundle-action@main - with: - target: 'deno' - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - # Replace links to other packages with links to the deno branch: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/deno/"; - - # Replace reference to `@stdlib/types` with CDN link: - find ./deno -type f -name '*.ts' -print0 | xargs -0 -r sed -Ei "s/\/\/\/ /\/\/\/ /g" - - # Change wording of project description to avoid reference to JavaScript and Node.js: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "s/a standard library for JavaScript and Node.js, /a standard library /g" - - # Rewrite all `require()`s to use jsDelivr links: - find ./deno -type f -name '*.md' -print0 | xargs -0 sed -Ei "/require\( '@stdlib\// { - s/(var|let|const)\s+([a-z0-9_]+)\s+=\s*require\( '([^']+)' \);/import \2 from \'\3\';/i - s/@stdlib/https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js/ - s/';/@deno\/mod.js';/ - }" - - # Rewrite first `import` to show importing of named exports if available: - exports=$(cat lib/index.js | \ - grep -E 'setReadOnly\(.*,.*,.*\)' | \ - sed -E 's/setReadOnly\((.*),(.*),(.*)\);/\2/' | \ - sed -E "s/'//g" | \ - sort) - if [ -n "$exports" ]; then - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\nimport\s+([a-zA-Z0-9_]+)\s+from\s*'([^']+)';\n\`\`\`/\`\`\`javascript\nimport \1 from '\2';\n\`\`\`\n\nYou can also import the following named exports from the package:\n\n\`\`\`javascript\nimport { $(echo $exports | sed -E 's/ /, /g') } from '\2';\n\`\`\`/" - fi - - # Remove `installation`, `cli`, and `c` sections: - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./deno -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Create package.json file for deno branch: - jq --indent 2 '{"name": .name, "version": .version, "description": .description, "license": .license, "type": "module", "main": "./mod.js", "homepage": .homepage, "repository": .repository, "bugs": .bugs, "keywords": .keywords, "funding": .funding}' package.json > ./deno/package.json - - # Delete everything in current directory aside from deno folder: - - name: 'Delete everything in current directory aside from deno folder' - run: | - find . -type 'f' | grep -v -e "deno" -e ".git/" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e "deno" -e ".git" | xargs -r rm -rf - - # Move deno directory to root: - - name: 'Move deno directory to root' - run: | - mv ./deno/* . - rmdir ./deno - - # Commit changes: - - name: 'Commit changes' - run: | - git add -A - git commit -m "Auto-generated commit" - - # Push changes to `deno` branch: - - name: 'Push changes to `deno` branch' - run: | - SLUG=${{ github.repository }} - echo "Pushing changes to $SLUG..." - git push "https://$GITHUB_ACTOR:$GITHUB_TOKEN@github.com/$SLUG.git" deno - - # Send status to Slack channel if job fails: - - name: 'Send status to Slack channel in case of failure' - # Pin action to full length commit SHA - uses: 8398a7/action-slack@28ba43ae48961b90635b50953d216767a6bea486 # v3.16.2 - with: - status: ${{ job.status }} - channel: '#npm-ci' - if: failure() - - # Define job to create a UMD bundle... - umd: - - # Define display name: - name: 'Create UMD bundle' - - # Define the type of virtual host machine on which to run the job: - runs-on: ubuntu-latest - - # Indicate that this job depends on the test job finishing: - needs: test - - # Define the sequence of job steps... - steps: - # Checkout the repository: - - name: 'Checkout repository' - # Pin action to full length commit SHA - uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0 - - # Configure Git: - - name: 'Configure Git' - run: | - git config --local user.email "noreply@stdlib.io" - git config --local user.name "stdlib-bot" - - # Check if remote `umd` branch exists: - - name: 'Check if remote `umd` branch exists' - id: umd-branch-exists - continue-on-error: true - run: | - git fetch --all - git ls-remote --exit-code --heads origin umd - if [ $? -eq 0 ]; then - echo "remote-exists=true" >> $GITHUB_OUTPUT - else - echo "remote-exists=false" >> $GITHUB_OUTPUT - fi - - # If `umd` exists, delete everything in branch and merge `production` into it - - name: 'If `umd` exists, delete everything in branch and merge `production` into it' - if: steps.umd-branch-exists.outputs.remote-exists - run: | - git checkout -b umd origin/umd - - find . -type 'f' | grep -v -e ".git/" -e "package.json" -e "README.md" -e "LICENSE" -e "CONTRIBUTORS" -e "NOTICE" | xargs -r rm - find . -mindepth 1 -type 'd' | grep -v -e ".git" | xargs -r rm -rf - - git add -A - git commit -m "Remove files" --allow-empty - - git config merge.theirs.name 'simulate `-s theirs`' - git config merge.theirs.driver 'cat %B > %A' - GIT_CONFIG_PARAMETERS="'merge.default=theirs'" git merge origin/production --allow-unrelated-histories - - # Copy files from `production` branch if necessary: - git checkout origin/production -- . - if [ -n "$(git status --porcelain)" ]; then - git add -A - git commit -m "Auto-generated commit" - fi - - # If `umd` does not exist, create `umd` branch: - - name: 'If `umd` does not exist, create `umd` branch' - if: ${{ steps.umd-branch-exists.outputs.remote-exists == false }} - run: | - git checkout production - git checkout -b umd - - # Copy files to umd directory: - - name: 'Copy files to umd directory' - run: | - mkdir -p umd - cp README.md LICENSE CONTRIBUTORS NOTICE ./umd - - # Install Node.js - - name: 'Install Node.js' - # Pin action to full length commit SHA - uses: actions/setup-node@b39b52d1213e96004bfcb1c61a8a6fa8ab84f3e8 # v4.0.1 - with: - node-version: 20 - timeout-minutes: 5 - - # Install dependencies: - - name: 'Install production and development dependencies' - id: install - run: | - npm install || npm install || npm install - timeout-minutes: 15 - - # Extract alias: - - name: 'Extract alias' - id: extract-alias - run: | - alias=$(grep -E 'require\(' README.md | head -n 1 | sed -E 's/^var ([a-zA-Z0-9_]+) = .+/\1/') - echo "alias=${alias}" >> $GITHUB_OUTPUT - - # Create Universal Module Definition (UMD) Node.js bundle: - - name: 'Create Universal Module Definition (UMD) Node.js bundle' - id: umd-bundle-node - uses: stdlib-js/bundle-action@main - with: - target: 'umd-node' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Create Universal Module Definition (UMD) browser bundle: - - name: 'Create Universal Module Definition (UMD) browser bundle' - id: umd-bundle-browser - uses: stdlib-js/bundle-action@main - with: - target: 'umd-browser' - alias: ${{ steps.extract-alias.outputs.alias }} - - # Rewrite file contents: - - name: 'Rewrite file contents' - run: | - - # Replace links to other packages with links to the umd branch: - find ./umd -type f -name '*.md' -print0 | xargs -0 sed -Ei "/\/tree\/main/b; /^\[@stdlib[^:]+: https:\/\/github.com\/stdlib-js\// s/(.*)/\\1\/tree\/umd/"; - - # Remove `installation`, `cli`, and `c` sections: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/
[^<]+<\/section>//g;" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.cli \-\->//g" - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/(\* \* \*\n+)?
[\s\S]+<\!\-\- \/.c \-\->//g" - - # Rewrite first `require()` to show consumption of the UMD bundle in Observable and via a `script` tag: - find ./umd -type f -name '*.md' -print0 | xargs -0 perl -0777 -i -pe "s/\`\`\`javascript\n(var|let|const)\s+([a-zA-Z0-9_]+)\s+=\s*require\( '\@stdlib\/([^']+)' \);\n\`\`\`/To use in Observable,\n\n\`\`\`javascript\n\2 = require\( 'https:\/\/cdn.jsdelivr.net\/gh\/stdlib-js\/\3\@umd\/browser.js' \)\n\`\`\`\n\nTo vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:\n\n\`\`\`javascript\nvar \2 = require\( 'path\/to\/vendor\/umd\/\3\/index.js' \)\n\`\`\`\n\nTo include the bundle in a webpage,\n\n\`\`\`html\n + + ```
@@ -227,7 +224,7 @@ console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ## Notice -This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. +This package is part of [stdlib][stdlib], a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. diff --git a/SECURITY.md b/SECURITY.md deleted file mode 100644 index 9702d4c..0000000 --- a/SECURITY.md +++ /dev/null @@ -1,5 +0,0 @@ -# Security - -> Policy for reporting security vulnerabilities. - -See the security policy [in the main project repository](https://github.com/stdlib-js/stdlib/security). diff --git a/branches.md b/branches.md deleted file mode 100644 index fa0c518..0000000 --- a/branches.md +++ /dev/null @@ -1,56 +0,0 @@ - - -# Branches - -This repository has the following branches: - -- **main**: default branch generated from the [stdlib project][stdlib-url], where all development takes place. -- **production**: [production build][production-url] of the package (e.g., reformatted error messages to reduce bundle sizes and thus the number of bytes transmitted over a network). -- **esm**: [ES Module][esm-url] branch for use via a `script` tag without the need for installation and bundlers (see [README][esm-readme]). -- **deno**: [Deno][deno-url] branch for use in Deno (see [README][deno-readme]). -- **umd**: [UMD][umd-url] branch for use in Observable, or in dual browser/Node.js environments (see [README][umd-readme]). - -The following diagram illustrates the relationships among the above branches: - -```mermaid -graph TD; -A[stdlib]-->|generate standalone package|B; -B[main] -->|productionize| C[production]; -C -->|bundle| D[esm]; -C -->|bundle| E[deno]; -C -->|bundle| F[umd]; - -%% click A href "https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray" -%% click B href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/main" -%% click C href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production" -%% click D href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm" -%% click E href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno" -%% click F href "https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd" -``` - -[stdlib-url]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-reduce-subarray -[production-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/production -[deno-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/deno -[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/deno/README.md -[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/umd -[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/umd/README.md -[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/tree/esm -[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray/blob/esm/README.md \ No newline at end of file diff --git a/dist/0d.js b/dist/0d.js deleted file mode 100644 index 90f58ee..0000000 --- a/dist/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/dist/0d_accessors.js b/dist/0d_accessors.js deleted file mode 100644 index dd7234c..0000000 --- a/dist/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/dist/10d.js b/dist/10d.js deleted file mode 100644 index fa92d91..0000000 --- a/dist/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/dist/10d_accessors.js b/dist/10d_accessors.js deleted file mode 100644 index 3f60306..0000000 --- a/dist/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/dist/10d_blocked.js b/dist/10d_blocked.js deleted file mode 100644 index 237f221..0000000 --- a/dist/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9[ k ] = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/dist/10d_blocked_accessors.js b/dist/10d_blocked_accessors.js deleted file mode 100644 index 5eb131b..0000000 --- a/dist/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9[ k ] = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/dist/1d.js b/dist/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/dist/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/dist/1d_accessors.js b/dist/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/dist/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/dist/2d.js b/dist/2d.js deleted file mode 100644 index dade268..0000000 --- a/dist/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/dist/2d_accessors.js b/dist/2d_accessors.js deleted file mode 100644 index bc3026d..0000000 --- a/dist/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/dist/2d_blocked.js b/dist/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/dist/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/dist/2d_blocked_accessors.js b/dist/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/dist/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/dist/3d.js b/dist/3d.js deleted file mode 100644 index a8f6c6e..0000000 --- a/dist/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/dist/3d_accessors.js b/dist/3d_accessors.js deleted file mode 100644 index 44fc164..0000000 --- a/dist/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/dist/3d_blocked.js b/dist/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/dist/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/dist/3d_blocked_accessors.js b/dist/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/dist/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/dist/4d.js b/dist/4d.js deleted file mode 100644 index 63d7e9e..0000000 --- a/dist/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/dist/4d_accessors.js b/dist/4d_accessors.js deleted file mode 100644 index c212572..0000000 --- a/dist/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/dist/4d_blocked.js b/dist/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/dist/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/dist/4d_blocked_accessors.js b/dist/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/dist/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/dist/5d.js b/dist/5d.js deleted file mode 100644 index 9c7e7aa..0000000 --- a/dist/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/dist/5d_accessors.js b/dist/5d_accessors.js deleted file mode 100644 index fe9a796..0000000 --- a/dist/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/dist/5d_blocked.js b/dist/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/dist/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/dist/5d_blocked_accessors.js b/dist/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/dist/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/dist/6d.js b/dist/6d.js deleted file mode 100644 index a296861..0000000 --- a/dist/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/dist/6d_accessors.js b/dist/6d_accessors.js deleted file mode 100644 index cafbe6e..0000000 --- a/dist/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/dist/6d_blocked.js b/dist/6d_blocked.js deleted file mode 100644 index f11bfe8..0000000 --- a/dist/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/dist/6d_blocked_accessors.js b/dist/6d_blocked_accessors.js deleted file mode 100644 index 9acf3c2..0000000 --- a/dist/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/dist/7d.js b/dist/7d.js deleted file mode 100644 index 87df811..0000000 --- a/dist/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/dist/7d_accessors.js b/dist/7d_accessors.js deleted file mode 100644 index 468524a..0000000 --- a/dist/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/dist/7d_blocked.js b/dist/7d_blocked.js deleted file mode 100644 index 1e63eb6..0000000 --- a/dist/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/dist/7d_blocked_accessors.js b/dist/7d_blocked_accessors.js deleted file mode 100644 index e60375e..0000000 --- a/dist/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/dist/8d.js b/dist/8d.js deleted file mode 100644 index 35ec78a..0000000 --- a/dist/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/dist/8d_accessors.js b/dist/8d_accessors.js deleted file mode 100644 index 8d18558..0000000 --- a/dist/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/dist/8d_blocked.js b/dist/8d_blocked.js deleted file mode 100644 index cb21b57..0000000 --- a/dist/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/dist/8d_blocked_accessors.js b/dist/8d_blocked_accessors.js deleted file mode 100644 index d868c12..0000000 --- a/dist/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/dist/9d.js b/dist/9d.js deleted file mode 100644 index 14509e8..0000000 --- a/dist/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/dist/9d_accessors.js b/dist/9d_accessors.js deleted file mode 100644 index 355ed51..0000000 --- a/dist/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/dist/9d_blocked.js b/dist/9d_blocked.js deleted file mode 100644 index fd076cd..0000000 --- a/dist/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/dist/9d_blocked_accessors.js b/dist/9d_blocked_accessors.js deleted file mode 100644 index 6471aa1..0000000 --- a/dist/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/dist/factory.js b/dist/factory.js deleted file mode 100644 index 7d3848a..0000000 --- a/dist/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/string-format' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/dist/increment_offsets.js b/dist/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/dist/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/dist/index.js b/dist/index.js deleted file mode 100644 index bc40bcf..0000000 --- a/dist/index.js +++ /dev/null @@ -1,129 +0,0 @@ -/** @license Apache-2.0 */ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property/dist' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/dist/index.js.map b/dist/index.js.map deleted file mode 100644 index 9731d50..0000000 --- a/dist/index.js.map +++ /dev/null @@ -1,7 +0,0 @@ -{ - "version": 3, - "sources": ["../lib/initialize_array_views.js", "../lib/increment_offsets.js", "../lib/set_view_offsets.js", "../lib/offsets.js", "../lib/2d_blocked_accessors.js", "../lib/3d_blocked_accessors.js", "../lib/4d_blocked_accessors.js", "../lib/5d_blocked_accessors.js", "../lib/6d_blocked_accessors.js", "../lib/7d_blocked_accessors.js", "../lib/8d_blocked_accessors.js", "../lib/9d_blocked_accessors.js", "../lib/10d_blocked_accessors.js", "../lib/2d_blocked.js", "../lib/3d_blocked.js", "../lib/4d_blocked.js", "../lib/5d_blocked.js", "../lib/6d_blocked.js", "../lib/7d_blocked.js", "../lib/8d_blocked.js", "../lib/9d_blocked.js", "../lib/10d_blocked.js", "../lib/0d_accessors.js", "../lib/1d_accessors.js", "../lib/2d_accessors.js", "../lib/3d_accessors.js", "../lib/4d_accessors.js", "../lib/5d_accessors.js", "../lib/6d_accessors.js", "../lib/7d_accessors.js", "../lib/8d_accessors.js", "../lib/9d_accessors.js", "../lib/10d_accessors.js", "../lib/nd_accessors.js", "../lib/0d.js", "../lib/1d.js", "../lib/2d.js", "../lib/3d.js", "../lib/4d.js", "../lib/5d.js", "../lib/6d.js", "../lib/7d.js", "../lib/8d.js", "../lib/9d.js", "../lib/10d.js", "../lib/nd.js", "../lib/main.js", "../lib/factory.js", "../lib/index.js"], - "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = initializeViews;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nmodule.exports = incrementOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nmodule.exports = setViewOffsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = offsets;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9[ k ] = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' );\nvar blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' );\nvar takeIndexed = require( '@stdlib/array-base-take-indexed' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9[ k ] = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = blockedunary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' );\n* var accessors = require( '@stdlib/array-base-accessors' );\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar without = require( '@stdlib/array-base-without' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary0d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary1d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary2d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary3d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary4d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary5d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary6d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary7d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary8d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary9d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nvar incrementOffsets = require( './increment_offsets.js' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unary10d;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar vind2bind = require( '@stdlib/ndarray-base-vind2bind' );\nvar zeros = require( '@stdlib/array-base-zeros' );\nvar setViewOffsets = require( './set_view_offsets.js' );\nvar offsets = require( './offsets.js' );\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = unarynd;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' );\nvar normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' );\nvar indicesComplement = require( '@stdlib/array-base-indices-complement' );\nvar takeIndexed2 = require( '@stdlib/array-base-take-indexed2' );\nvar iterationOrder = require( '@stdlib/ndarray-base-iteration-order' );\nvar strides2order = require( '@stdlib/ndarray-base-strides2order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar join = require( '@stdlib/array-base-join' );\nvar format = require( '@stdlib/string-format' );\nvar initializeViews = require( './initialize_array_views.js' );\nvar blockedaccessorunary2d = require( './2d_blocked_accessors.js' );\nvar blockedaccessorunary3d = require( './3d_blocked_accessors.js' );\nvar blockedaccessorunary4d = require( './4d_blocked_accessors.js' );\nvar blockedaccessorunary5d = require( './5d_blocked_accessors.js' );\nvar blockedaccessorunary6d = require( './6d_blocked_accessors.js' );\nvar blockedaccessorunary7d = require( './7d_blocked_accessors.js' );\nvar blockedaccessorunary8d = require( './8d_blocked_accessors.js' );\nvar blockedaccessorunary9d = require( './9d_blocked_accessors.js' );\nvar blockedaccessorunary10d = require( './10d_blocked_accessors.js' );\nvar blockedunary2d = require( './2d_blocked.js' );\nvar blockedunary3d = require( './3d_blocked.js' );\nvar blockedunary4d = require( './4d_blocked.js' );\nvar blockedunary5d = require( './5d_blocked.js' );\nvar blockedunary6d = require( './6d_blocked.js' );\nvar blockedunary7d = require( './7d_blocked.js' );\nvar blockedunary8d = require( './8d_blocked.js' );\nvar blockedunary9d = require( './9d_blocked.js' );\nvar blockedunary10d = require( './10d_blocked.js' );\nvar accessorunary0d = require( './0d_accessors.js' );\nvar accessorunary1d = require( './1d_accessors.js' );\nvar accessorunary2d = require( './2d_accessors.js' );\nvar accessorunary3d = require( './3d_accessors.js' );\nvar accessorunary4d = require( './4d_accessors.js' );\nvar accessorunary5d = require( './5d_accessors.js' );\nvar accessorunary6d = require( './6d_accessors.js' );\nvar accessorunary7d = require( './7d_accessors.js' );\nvar accessorunary8d = require( './8d_accessors.js' );\nvar accessorunary9d = require( './9d_accessors.js' );\nvar accessorunary10d = require( './10d_accessors.js' );\nvar accessorunarynd = require( './nd_accessors.js' );\nvar unary0d = require( './0d.js' );\nvar unary1d = require( './1d.js' );\nvar unary2d = require( './2d.js' );\nvar unary3d = require( './3d.js' );\nvar unary4d = require( './4d.js' );\nvar unary5d = require( './5d.js' );\nvar unary6d = require( './6d.js' );\nvar unary7d = require( './7d.js' );\nvar unary8d = require( './8d.js' );\nvar unary9d = require( './9d.js' );\nvar unary10d = require( './10d.js' );\nvar unarynd = require( './nd.js' );\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = unaryReduceSubarray;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar isFunction = require( '@stdlib/assert-is-function' );\nvar format = require( '@stdlib/string-format' );\nvar reduce = require( './main.js' );\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'invalid argument. First argument must be a function. Value: `%s`.', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nmodule.exports = factory;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var every = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var filled = require( '@stdlib/array-base-filled' );\n* var ndarray2array = require( '@stdlib/ndarray-base-to-array' );\n* var base = require( '@stdlib/ndarray-base-every' );\n* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' );\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nvar setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' );\nvar main = require( './main.js' );\nvar factory = require( './factory.js' );\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n\n// exports: { \"factory\": \"main.factory\" }\n"], - "mappings": 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"accessorunary10d", "accessorunarynd", "unary0d", "unary1d", "unary2d", "unary3d", "unary4d", "unary5d", "unary6d", "unary7d", "unary8d", "unary9d", "unary10d", "unarynd", "UNARY", "ACCESSOR_UNARY", "BLOCKED_UNARY", "BLOCKED_ACCESSOR_UNARY", "MAX_DIMS", "unaryReduceSubarray", "fcn", "arrays", "dims", "options", "views", "ndims", "ldims", "opts", "arr", "tmp", "len", "shx", "shc", "shl", "iox", "ioy", "ord", "sc", "sl", "sy", "ns", "d", "s", "N", "M", "K", "x", "y", "i", "j", "require_factory", "__commonJSMin", "exports", "module", "isFunction", "format", "reduce", "factory", "fcn", "reducer", "arrays", "dims", "options", "opts", "setReadOnly", "main", "factory"] -} diff --git a/dist/initialize_array_views.js b/dist/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/dist/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/dist/main.js b/dist/main.js deleted file mode 100644 index 5bfdc85..0000000 --- a/dist/main.js +++ /dev/null @@ -1,469 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var strides2order = require( '@stdlib/ndarray-base-strides2order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/string-format' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var ord; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - ord = strides2order( sl ); - if ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/dist/nd.js b/dist/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/dist/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/dist/nd_accessors.js b/dist/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/dist/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/dist/offsets.js b/dist/offsets.js deleted file mode 100644 index a606628..0000000 --- a/dist/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/dist/set_view_offsets.js b/dist/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/dist/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/docs/repl.txt b/docs/repl.txt deleted file mode 100644 index c2b8b99..0000000 --- a/docs/repl.txt +++ /dev/null @@ -1,86 +0,0 @@ - -{{alias}}( fcn, arrays, dims[, options] ) - Performs a reduction over a list of specified dimensions in an input ndarray - and assigns results to a provided output ndarray. - - Each provided "ndarray" should be an object with the following properties: - - - dtype: data type. - - data: data buffer. - - shape: dimensions. - - strides: stride lengths. - - offset: index offset. - - order: specifies whether an ndarray is row-major (C-style) or column-major - (Fortran-style). - - The output ndarray and any additional ndarray arguments are expected to have - the same dimensions as the non-reduced dimensions of the input ndarray. When - calling the reduction function, any additional ndarray arguments are - provided as zero-dimensional ndarray-like objects. - - Parameters - ---------- - fcn: Function - Function which will be applied to a subarray and should reduce the - subarray to a single scalar value. The function should have the - following signature: - - fcn( arrays[, options] ) - - where - - - arrays: array containing a subarray of the input ndarray and any - additional ndarray arguments as zero-dimensional ndarrays. - - options: function options. - - arrays: ArrayLikeObject - Array-like object containing one input ndarray and one output ndarray, - followed by any additional ndarray arguments. - - dims: Array - List of dimensions over which to perform a reduction. - - options: Object (optional) - Function options. - - Examples - -------- - // Define ndarray data and meta data... - > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); - > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0 ] ); - > var dtype = 'float64'; - > var shx = [ 2, 2 ]; - > var shy = []; - > var sx = [ 2, 1 ]; - > var sy = [ 0 ]; - > var ox = 0; - > var oy = 0; - > var order = 'row-major'; - - // Define a trivial reduction function... - > function fcn( arrays ) { return arrays[0].data[ arrays[0].offset ]; }; - - // Using minimal ndarray-like objects... - > var x = { - ... 'dtype': dtype, - ... 'data': xbuf, - ... 'shape': shx, - ... 'strides': sx, - ... 'offset': ox, - ... 'order': order - ... }; - > var y = { - ... 'dtype': dtype, - ... 'data': ybuf, - ... 'shape': shy, - ... 'strides': sy, - ... 'offset': oy, - ... 'order': order - ... }; - > {{alias}}( fcn, [ x, y ], [ 0, 1 ] ); - > y.data - [ 1.0 ] - - See Also - -------- - diff --git a/examples/index.js b/examples/index.js deleted file mode 100644 index 5786a52..0000000 --- a/examples/index.js +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); -var filled = require( '@stdlib/array-base-filled' ); -var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -var every = require( '@stdlib/ndarray-base-every' ); -var unaryReduceSubarray = require( './../lib' ); - -var N = 10; -var x = { - 'dtype': 'generic', - 'data': discreteUniform( N, -5, 5, { - 'dtype': 'generic' - }), - 'shape': [ 1, 5, 2 ], - 'strides': [ 10, 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; -var y = { - 'dtype': 'generic', - 'data': filled( false, 2 ), - 'shape': [ 1, 2 ], - 'strides': [ 2, 1 ], - 'offset': 0, - 'order': 'row-major' -}; - -unaryReduceSubarray( every, [ x, y ], [ 1 ] ); - -console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); -console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); diff --git a/index.mjs b/index.mjs new file mode 100644 index 0000000..5ec385a --- /dev/null +++ b/index.mjs @@ -0,0 +1,4 @@ +// Copyright (c) 2025 The Stdlib Authors. License is Apache-2.0: http://www.apache.org/licenses/LICENSE-2.0 +/// +import r from"https://cdn.jsdelivr.net/gh/stdlib-js/utils-define-nonenumerable-read-only-property@v0.2.1-esm/index.mjs";import s from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-ndarraylike2object@v0.2.2-esm/index.mjs";import o from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-unique-normalized-indices@esm/index.mjs";import f from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-indices-complement@esm/index.mjs";import e from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed2@esm/index.mjs";import t from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-iteration-order@v0.2.2-esm/index.mjs";import h from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2order@v0.2.2-esm/index.mjs";import p from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel@v0.2.2-esm/index.mjs";import u from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-join@v0.1.1-esm/index.mjs";import n from"https://cdn.jsdelivr.net/gh/stdlib-js/error-tools-fmtprodmsg@v0.2.2-esm/index.mjs";import d from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-loop-interchange-order@v0.2.1-esm/index.mjs";import i from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-tiling-block-size@v0.2.2-esm/index.mjs";import a from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-take-indexed@v0.2.2-esm/index.mjs";import l from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@v0.2.2-esm/index.mjs";import c from"https://cdn.jsdelivr.net/gh/stdlib-js/array-base-without@esm/index.mjs";import m from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@v0.2.2-esm/index.mjs";import g from"https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-vind2bind@esm/index.mjs";import v from"https://cdn.jsdelivr.net/gh/stdlib-js/assert-is-function@v0.2.2-esm/index.mjs";function y(r,s){var o;for(o=0;o0;){for(k0;){for(P0;){for(q0;){for(V0;){for(T0;){for(D0;){for(C0;){for(B0;){for(R0;){for(K0;){for(J0;){for(H0;){for(G0;){for(F0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for(K0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(Q0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(z0;){for(k0;){for(I0;){for(q0;){for(V0;){for(F0;){for(D0;){for(C0;){for(B0;){for(L0;){for(K0;){for(J0;){for(H0;){for(G0;){for(U0;){for(S0;){for(Q0;){for(O0;){for(M0;){for(L0;){for($0;){for(Z0;){for(Y0;){for(X0;){for(W0;){for(U0;){for(S0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(_0;){for($0;){for(Z0;){for(Y0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er0;){for(fr0;){for(or0;){for(sr0;){for(rr0;){for(lr0;){for(ar0;){for(ir0;){for(dr0;){for(nr0;){for(ur0;){for(pr0;){for(hr0;){for(tr0;){for(er3?a:{},O=d.length,T=[],X=0;Xv)throw new RangeError(n("invalid argument. 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Value: [%s].",v,u(i,",")));for(S=v-Q,X=1;X2?f:{};return A(r,s,o,e)}}r(A,"factory",T);export{A as default,T as factory}; +//# sourceMappingURL=index.mjs.map diff --git a/index.mjs.map b/index.mjs.map new file mode 100644 index 0000000..997e1e5 --- /dev/null +++ b/index.mjs.map @@ -0,0 +1 @@ +{"version":3,"file":"index.mjs","sources":["../lib/increment_offsets.js","../lib/set_view_offsets.js","../lib/offsets.js","../lib/nd_accessors.js","../lib/nd.js","../lib/main.js","../lib/0d.js","../lib/1d.js","../lib/2d.js","../lib/3d.js","../lib/4d.js","../lib/5d.js","../lib/6d.js","../lib/7d.js","../lib/8d.js","../lib/9d.js","../lib/10d.js","../lib/0d_accessors.js","../lib/1d_accessors.js","../lib/2d_accessors.js","../lib/3d_accessors.js","../lib/4d_accessors.js","../lib/5d_accessors.js","../lib/6d_accessors.js","../lib/7d_accessors.js","../lib/8d_accessors.js","../lib/9d_accessors.js","../lib/10d_accessors.js","../lib/2d_blocked.js","../lib/3d_blocked.js","../lib/4d_blocked.js","../lib/5d_blocked.js","../lib/6d_blocked.js","../lib/7d_blocked.js","../lib/8d_blocked.js","../lib/9d_blocked.js","../lib/10d_blocked.js","../lib/2d_blocked_accessors.js","../lib/3d_blocked_accessors.js","../lib/4d_blocked_accessors.js","../lib/5d_blocked_accessors.js","../lib/6d_blocked_accessors.js","../lib/7d_blocked_accessors.js","../lib/8d_blocked_accessors.js","../lib/9d_blocked_accessors.js","../lib/10d_blocked_accessors.js","../lib/initialize_array_views.js","../lib/factory.js","../lib/index.js"],"sourcesContent":["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Increments index offsets according to a list of increments.\n*\n* ## Notes\n*\n* - This function mutates the list of index offsets.\n*\n* @private\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @param {NonNegativeIntegerArray} inc - list of increments\n* @returns {NonNegativeIntegerArray} updated offsets\n*/\nfunction incrementOffsets( offsets, inc ) {\n\tvar i;\n\tfor ( i = 0; i < offsets.length; i++ ) {\n\t\toffsets[ i ] += inc[ i ];\n\t}\n\treturn offsets;\n}\n\n\n// EXPORTS //\n\nexport default incrementOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Sets view offsets according to a list of index offsets.\n*\n* ## Notes\n*\n* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements.\n* - This function mutates the provides view objects.\n*\n* @private\n* @param {Array} views - list of ndarray-like objects representing ndarray views\n* @param {NonNegativeIntegerArray} offsets - list of index offsets\n* @returns {Array} updated views\n*/\nfunction setViewOffsets( views, offsets ) {\n\tvar i;\n\tvar j;\n\tfor ( i = 0, j = 0; i < offsets.length; i++ ) {\n\t\tif ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view\n\t\t\tcontinue;\n\t\t}\n\t\tviews[ j ].offset = offsets[ i ];\n\t\tj += 1;\n\t}\n\treturn views;\n}\n\n\n// EXPORTS //\n\nexport default setViewOffsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Resolves index offsets from a list of ndarray-like objects.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @returns {NonNegativeIntegerArray} list of offsets\n*/\nfunction offsets( arrays ) {\n\tvar out = [];\n\tvar i;\n\tfor ( i = 0; i < arrays.length; i++ ) {\n\t\tout.push( arrays[ i ].offset );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default offsets;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar set;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tset( ybuf, io[1], fcn( views, opts ) );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport numel from '@stdlib/ndarray-base-numel';\nimport vind2bind from '@stdlib/ndarray-base-vind2bind';\nimport zeros from '@stdlib/array-base-zeros';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// VARIABLES //\n\nvar MODE = 'throw';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unarynd( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unarynd( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar len;\n\tvar sh;\n\tvar iv;\n\tvar io;\n\tvar N;\n\tvar v;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tN = arrays.length;\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Compute the total number of elements over which to iterate:\n\tlen = numel( sh );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...\n\tio = zeros( N );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tv = arrays[ j ];\n\t\t\tio[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE );\n\t\t}\n\t\tsetViewOffsets( views, io );\n\t\tybuf[ io[1] ] = fcn( views, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unarynd;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport ndarray2object from '@stdlib/ndarray-base-ndarraylike2object';\nimport normalizeIndices from '@stdlib/ndarray-base-to-unique-normalized-indices';\nimport indicesComplement from '@stdlib/array-base-indices-complement';\nimport takeIndexed2 from '@stdlib/array-base-take-indexed2';\nimport iterationOrder from '@stdlib/ndarray-base-iteration-order';\nimport strides2order from '@stdlib/ndarray-base-strides2order';\nimport numel from '@stdlib/ndarray-base-numel';\nimport join from '@stdlib/array-base-join';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport initializeViews from './initialize_array_views.js';\nimport blockedaccessorunary2d from './2d_blocked_accessors.js';\nimport blockedaccessorunary3d from './3d_blocked_accessors.js';\nimport blockedaccessorunary4d from './4d_blocked_accessors.js';\nimport blockedaccessorunary5d from './5d_blocked_accessors.js';\nimport blockedaccessorunary6d from './6d_blocked_accessors.js';\nimport blockedaccessorunary7d from './7d_blocked_accessors.js';\nimport blockedaccessorunary8d from './8d_blocked_accessors.js';\nimport blockedaccessorunary9d from './9d_blocked_accessors.js';\nimport blockedaccessorunary10d from './10d_blocked_accessors.js';\nimport blockedunary2d from './2d_blocked.js';\nimport blockedunary3d from './3d_blocked.js';\nimport blockedunary4d from './4d_blocked.js';\nimport blockedunary5d from './5d_blocked.js';\nimport blockedunary6d from './6d_blocked.js';\nimport blockedunary7d from './7d_blocked.js';\nimport blockedunary8d from './8d_blocked.js';\nimport blockedunary9d from './9d_blocked.js';\nimport blockedunary10d from './10d_blocked.js';\nimport accessorunary0d from './0d_accessors.js';\nimport accessorunary1d from './1d_accessors.js';\nimport accessorunary2d from './2d_accessors.js';\nimport accessorunary3d from './3d_accessors.js';\nimport accessorunary4d from './4d_accessors.js';\nimport accessorunary5d from './5d_accessors.js';\nimport accessorunary6d from './6d_accessors.js';\nimport accessorunary7d from './7d_accessors.js';\nimport accessorunary8d from './8d_accessors.js';\nimport accessorunary9d from './9d_accessors.js';\nimport accessorunary10d from './10d_accessors.js';\nimport accessorunarynd from './nd_accessors.js';\nimport unary0d from './0d.js';\nimport unary1d from './1d.js';\nimport unary2d from './2d.js';\nimport unary3d from './3d.js';\nimport unary4d from './4d.js';\nimport unary5d from './5d.js';\nimport unary6d from './6d.js';\nimport unary7d from './7d.js';\nimport unary8d from './8d.js';\nimport unary9d from './9d.js';\nimport unary10d from './10d.js';\nimport unarynd from './nd.js';\n\n\n// VARIABLES //\n\nvar UNARY = [\n\tunary0d,\n\tunary1d,\n\tunary2d,\n\tunary3d,\n\tunary4d,\n\tunary5d,\n\tunary6d,\n\tunary7d,\n\tunary8d,\n\tunary9d,\n\tunary10d\n];\nvar ACCESSOR_UNARY = [\n\taccessorunary0d,\n\taccessorunary1d,\n\taccessorunary2d,\n\taccessorunary3d,\n\taccessorunary4d,\n\taccessorunary5d,\n\taccessorunary6d,\n\taccessorunary7d,\n\taccessorunary8d,\n\taccessorunary9d,\n\taccessorunary10d\n];\nvar BLOCKED_UNARY = [\n\tblockedunary2d, // 0\n\tblockedunary3d,\n\tblockedunary4d,\n\tblockedunary5d,\n\tblockedunary6d,\n\tblockedunary7d,\n\tblockedunary8d,\n\tblockedunary9d,\n\tblockedunary10d // 8\n];\nvar BLOCKED_ACCESSOR_UNARY = [\n\tblockedaccessorunary2d, // 0\n\tblockedaccessorunary3d,\n\tblockedaccessorunary4d,\n\tblockedaccessorunary5d,\n\tblockedaccessorunary6d,\n\tblockedaccessorunary7d,\n\tblockedaccessorunary8d,\n\tblockedaccessorunary9d,\n\tblockedaccessorunary10d // 8\n];\nvar MAX_DIMS = UNARY.length - 1;\n\n\n// MAIN //\n\n/**\n* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n* @param {Options} [options] - function options\n* @throws {Error} arrays must have the expected number of dimensions\n* @throws {RangeError} dimension indices must not exceed input ndarray bounds\n* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions\n* @throws {Error} must provide unique dimension indices\n* @throws {Error} arrays must have the same loop dimension sizes\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = [ false ];\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] );\n*\n* var v = y.data;\n* // returns [ true ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 12 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3, 2, 2 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 4, 2, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ]\n*/\nfunction unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements\n\tvar views;\n\tvar ndims;\n\tvar ldims;\n\tvar opts;\n\tvar arr;\n\tvar tmp;\n\tvar len;\n\tvar shx;\n\tvar shc;\n\tvar shl;\n\tvar iox;\n\tvar ioy;\n\tvar ord;\n\tvar sc;\n\tvar sl;\n\tvar sy;\n\tvar ns;\n\tvar d;\n\tvar s;\n\tvar N;\n\tvar M;\n\tvar K;\n\tvar x;\n\tvar y;\n\tvar i;\n\tvar j;\n\n\tif ( arguments.length > 3 ) {\n\t\topts = options;\n\t} else {\n\t\topts = {};\n\t}\n\t// Standardize ndarray meta data...\n\tN = arrays.length;\n\tarr = [];\n\tfor ( i = 0; i < N; i++ ) {\n\t\tarr.push( ndarray2object( arrays[ i ] ) );\n\t}\n\t// Cache references to the input and output arrays:\n\tx = arr[ 0 ];\n\ty = arr[ 1 ];\n\n\t// Resolve the number of input array dimensions:\n\tshx = x.shape;\n\tndims = shx.length;\n\n\t// Verify that we've been provided a list of unique dimension indices...\n\tM = dims.length;\n\td = normalizeIndices( dims, ndims-1 );\n\tif ( d === null ) {\n\t\tthrow new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\td.sort();\n\tif ( d.length !== M ) {\n\t\tthrow new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) );\n\t}\n\t// Check whether we've been provided a valid number of dimensions to reduce...\n\tif ( M > ndims ) {\n\t\tthrow new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) );\n\t}\n\t// Verify that provided ndarrays have the expected number of dimensions...\n\tK = ndims - M;\n\tfor ( i = 1; i < N; i++ ) {\n\t\tif ( arr[ i ].shape.length !== K ) {\n\t\t\tthrow new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) );\n\t\t}\n\t}\n\t// Determine whether we can avoid iteration altogether...\n\tif ( K === 0 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, opts );\n\t}\n\t// Resolve the non-reduced (\"loop\") dimensions and associated strides:\n\tldims = indicesComplement( shx.length, d );\n\ttmp = takeIndexed2( shx, x.strides, ldims );\n\tshl = tmp[ 0 ];\n\tsl = tmp[ 1 ];\n\n\t// Resolve the reduced (\"core\") dimensions and associated strides:\n\ttmp = takeIndexed2( shx, x.strides, d );\n\tshc = tmp[ 0 ];\n\tsc = tmp[ 1 ];\n\n\t// Verify that the provided arrays have the same loop dimensions...\n\tlen = 1; // number of elements\n\tns = 0; // number of singleton dimensions\n\tfor ( i = 0; i < K; i++ ) {\n\t\ts = shl[ i ];\n\t\tfor ( j = 1; j < N; j++ ) {\n\t\t\tif ( s !== arr[ j ].shape[ i ] ) {\n\t\t\t\tthrow new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) );\n\t\t\t}\n\t\t}\n\t\t// Note that, if one of the dimensions is `0`, the length will be `0`...\n\t\tlen *= s;\n\n\t\t// Check whether the current dimension is a singleton dimension...\n\t\tif ( s === 1 ) {\n\t\t\tns += 1;\n\t\t}\n\t}\n\t// Check whether we were provided empty ndarrays...\n\tif ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) {\n\t\treturn;\n\t}\n\t// Initialize ndarray-like objects for representing sub-array views...\n\tviews = [\n\t\t{\n\t\t\t'dtype': x.dtype,\n\t\t\t'data': x.data,\n\t\t\t'shape': shc,\n\t\t\t'strides': sc,\n\t\t\t'offset': x.offset,\n\t\t\t'order': x.order\n\t\t}\n\t];\n\tinitializeViews( arr, views );\n\n\t// Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration...\n\tif ( K === 1 ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, opts );\n\t}\n\tsy = y.strides;\n\n\t// Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration...\n\tif ( ns === K-1 ) {\n\t\t// Get the index of the non-singleton dimension...\n\t\tfor ( i = 0; i < K; i++ ) {\n\t\t\tif ( shl[ i ] !== 1 ) {\n\t\t\t\tbreak;\n\t\t\t}\n\t\t}\n\t\ty.shape = [ shl[i] ];\n\t\tfor ( j = 0; j < N; j++ ) {\n\t\t\tarr[ j ].strides = [ arr[j].strides[i] ];\n\t\t}\n\t\tsl = [ sl[i] ];\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn UNARY[ 1 ]( fcn, arr, views, sl, opts );\n\t}\n\tiox = iterationOrder( sl ); // +/-1\n\tioy = iterationOrder( sy ); // +/-1\n\n\t// Determine whether we can avoid blocked iteration...\n\tord = strides2order( sl );\n\tif ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len\n\t\t// So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration...\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t\t}\n\t\treturn UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts );\n\t}\n\t// At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration...\n\n\t// Determine whether we can perform blocked iteration...\n\tif ( K <= MAX_DIMS ) {\n\t\tif ( y.accessorProtocol ) {\n\t\t\treturn BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t\t}\n\t\treturn BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts );\n\t}\n\t// Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)...\n\tif ( y.accessorProtocol ) {\n\t\treturn accessorunarynd( fcn, arr, views, sl, opts );\n\t}\n\tunarynd( fcn, arr, views, sl, opts );\n}\n\n\n// EXPORTS //\n\nexport default unaryReduceSubarray;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 1 );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data;\n* // returns [ true ]\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tarrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1]) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport without from '@stdlib/array-base-without';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 1 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 2, 2 ];\n* var ysh = [];\n*\n* // Define the array strides:\n* var sx = [ 6, 1 ];\n* var sy = [ 0 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Perform a reduction:\n* unary0d( base, [ x, y ], {} );\n*\n* var v = y.data.get( 0 );\n* // returns true\n*/\nfunction unary0d( fcn, arrays, opts ) {\n\tvar y = arrays[ 1 ];\n\ty.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) );\n}\n\n\n// EXPORTS //\n\nexport default unary0d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 3, 2, 2 ];\n* var ysh = [ 3 ];\n*\n* // Define the array strides:\n* var sx = [ 4, 2, 1 ];\n* var sy = [ 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary1d( base, [ x, y ], views, [ 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ true, false, true ]\n*/\nfunction unary1d( fcn, arrays, views, strides, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar sh;\n\tvar S0;\n\tvar iv;\n\tvar i0;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables: dimensions and loop offset (pointer) increments...\n\tS0 = sh[ 0 ];\n\tdv0 = [ strides[0] ];\n\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\tdv0.push( arrays[i].strides[0] );\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\tsetViewOffsets( views, iv );\n\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\tincrementOffsets( iv, dv0 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary1d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction unary2d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 1 ];\n\t\tS1 = sh[ 0 ];\n\t\tdv0 = [ strides[1] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[1] );\n\t\t\tdv1.push( sv[0] - ( S0*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\tsetViewOffsets( views, iv );\n\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\tincrementOffsets( iv, dv0 );\n\t\t}\n\t\tincrementOffsets( iv, dv1 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction unary3d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 2 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 0 ];\n\t\tdv0 = [ strides[2] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[2] ) ];\n\t\tdv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[2] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[2] ) );\n\t\t\tdv2.push( sv[0] - ( S1*sv[1] ) );\n\t\t}\n\t} else {\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv1 );\n\t\t}\n\t\tincrementOffsets( iv, dv2 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction unary4d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 3 ];\n\t\tS1 = sh[ 2 ];\n\t\tS2 = sh[ 1 ];\n\t\tS3 = sh[ 0 ];\n\t\tdv0 = [ strides[3] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[2] - ( S0*strides[3] ) ];\n\t\tdv2 = [ strides[1] - ( S1*strides[2] ) ];\n\t\tdv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[3] );\n\t\t\tdv1.push( sv[2] - ( S0*sv[3] ) );\n\t\t\tdv2.push( sv[1] - ( S1*sv[2] ) );\n\t\t\tdv3.push( sv[0] - ( S2*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv2 );\n\t\t}\n\t\tincrementOffsets( iv, dv3 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction unary5d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 4 ];\n\t\tS1 = sh[ 3 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 1 ];\n\t\tS4 = sh[ 0 ];\n\t\tdv0 = [ strides[4] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[3] - ( S0*strides[4] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[3] ) ];\n\t\tdv3 = [ strides[1] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[4] );\n\t\t\tdv1.push( sv[3] - ( S0*sv[4] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[3] ) );\n\t\t\tdv3.push( sv[1] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[0] - ( S3*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv3 );\n\t\t}\n\t\tincrementOffsets( iv, dv4 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction unary6d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 5 ];\n\t\tS1 = sh[ 4 ];\n\t\tS2 = sh[ 3 ];\n\t\tS3 = sh[ 2 ];\n\t\tS4 = sh[ 1 ];\n\t\tS5 = sh[ 0 ];\n\t\tdv0 = [ strides[5] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[4] - ( S0*strides[5] ) ];\n\t\tdv2 = [ strides[3] - ( S1*strides[4] ) ];\n\t\tdv3 = [ strides[2] - ( S2*strides[3] ) ];\n\t\tdv4 = [ strides[1] - ( S3*strides[2] ) ];\n\t\tdv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[5] );\n\t\t\tdv1.push( sv[4] - ( S0*sv[5] ) );\n\t\t\tdv2.push( sv[3] - ( S1*sv[4] ) );\n\t\t\tdv3.push( sv[2] - ( S2*sv[3] ) );\n\t\t\tdv4.push( sv[1] - ( S3*sv[2] ) );\n\t\t\tdv5.push( sv[0] - ( S4*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv4 );\n\t\t}\n\t\tincrementOffsets( iv, dv5 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction unary7d( fcn, arrays, views, strides, isRowMajor, opts ) {\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 6 ];\n\t\tS1 = sh[ 5 ];\n\t\tS2 = sh[ 4 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 2 ];\n\t\tS5 = sh[ 1 ];\n\t\tS6 = sh[ 0 ];\n\t\tdv0 = [ strides[6] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[5] - ( S0*strides[6] ) ];\n\t\tdv2 = [ strides[4] - ( S1*strides[5] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[4] ) ];\n\t\tdv4 = [ strides[2] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[1] - ( S4*strides[2] ) ];\n\t\tdv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[6] );\n\t\t\tdv1.push( sv[5] - ( S0*sv[6] ) );\n\t\t\tdv2.push( sv[4] - ( S1*sv[5] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[4] ) );\n\t\t\tdv4.push( sv[2] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[1] - ( S4*sv[2] ) );\n\t\t\tdv6.push( sv[0] - ( S5*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv5 );\n\t\t}\n\t\tincrementOffsets( iv, dv6 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 7 ];\n\t\tS1 = sh[ 6 ];\n\t\tS2 = sh[ 5 ];\n\t\tS3 = sh[ 4 ];\n\t\tS4 = sh[ 3 ];\n\t\tS5 = sh[ 2 ];\n\t\tS6 = sh[ 1 ];\n\t\tS7 = sh[ 0 ];\n\t\tdv0 = [ strides[7] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[6] - ( S0*strides[7] ) ];\n\t\tdv2 = [ strides[5] - ( S1*strides[6] ) ];\n\t\tdv3 = [ strides[4] - ( S2*strides[5] ) ];\n\t\tdv4 = [ strides[3] - ( S3*strides[4] ) ];\n\t\tdv5 = [ strides[2] - ( S4*strides[3] ) ];\n\t\tdv6 = [ strides[1] - ( S5*strides[2] ) ];\n\t\tdv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[7] );\n\t\t\tdv1.push( sv[6] - ( S0*sv[7] ) );\n\t\t\tdv2.push( sv[5] - ( S1*sv[6] ) );\n\t\t\tdv3.push( sv[4] - ( S2*sv[5] ) );\n\t\t\tdv4.push( sv[3] - ( S3*sv[4] ) );\n\t\t\tdv5.push( sv[2] - ( S4*sv[3] ) );\n\t\t\tdv6.push( sv[1] - ( S5*sv[2] ) );\n\t\t\tdv7.push( sv[0] - ( S6*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv6 );\n\t\t}\n\t\tincrementOffsets( iv, dv7 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 8 ];\n\t\tS1 = sh[ 7 ];\n\t\tS2 = sh[ 6 ];\n\t\tS3 = sh[ 5 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 3 ];\n\t\tS6 = sh[ 2 ];\n\t\tS7 = sh[ 1 ];\n\t\tS8 = sh[ 0 ];\n\t\tdv0 = [ strides[8] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[7] - ( S0*strides[8] ) ];\n\t\tdv2 = [ strides[6] - ( S1*strides[7] ) ];\n\t\tdv3 = [ strides[5] - ( S2*strides[6] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[5] ) ];\n\t\tdv5 = [ strides[3] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[2] - ( S5*strides[3] ) ];\n\t\tdv7 = [ strides[1] - ( S6*strides[2] ) ];\n\t\tdv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[8] );\n\t\t\tdv1.push( sv[7] - ( S0*sv[8] ) );\n\t\t\tdv2.push( sv[6] - ( S1*sv[7] ) );\n\t\t\tdv3.push( sv[5] - ( S2*sv[6] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[5] ) );\n\t\t\tdv5.push( sv[3] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[2] - ( S5*sv[3] ) );\n\t\t\tdv7.push( sv[1] - ( S6*sv[2] ) );\n\t\t\tdv8.push( sv[0] - ( S7*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv7 );\n\t\t}\n\t\tincrementOffsets( iv, dv8 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar sh;\n\tvar S0;\n\tvar S1;\n\tvar S2;\n\tvar S3;\n\tvar S4;\n\tvar S5;\n\tvar S6;\n\tvar S7;\n\tvar S8;\n\tvar S9;\n\tvar sv;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar y;\n\tvar i;\n\n\t// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\t// Resolve the output ndarray and associated shape:\n\ty = arrays[ 1 ];\n\tsh = y.shape;\n\n\t// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...\n\tif ( isRowMajor ) {\n\t\t// For row-major ndarrays, the last dimensions have the fastest changing indices...\n\t\tS0 = sh[ 9 ];\n\t\tS1 = sh[ 8 ];\n\t\tS2 = sh[ 7 ];\n\t\tS3 = sh[ 6 ];\n\t\tS4 = sh[ 5 ];\n\t\tS5 = sh[ 4 ];\n\t\tS6 = sh[ 3 ];\n\t\tS7 = sh[ 2 ];\n\t\tS8 = sh[ 1 ];\n\t\tS9 = sh[ 0 ];\n\t\tdv0 = [ strides[9] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[8] - ( S0*strides[9] ) ];\n\t\tdv2 = [ strides[7] - ( S1*strides[8] ) ];\n\t\tdv3 = [ strides[6] - ( S2*strides[7] ) ];\n\t\tdv4 = [ strides[5] - ( S3*strides[6] ) ];\n\t\tdv5 = [ strides[4] - ( S4*strides[5] ) ];\n\t\tdv6 = [ strides[3] - ( S5*strides[4] ) ];\n\t\tdv7 = [ strides[2] - ( S6*strides[3] ) ];\n\t\tdv8 = [ strides[1] - ( S7*strides[2] ) ];\n\t\tdv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[9] );\n\t\t\tdv1.push( sv[8] - ( S0*sv[9] ) );\n\t\t\tdv2.push( sv[7] - ( S1*sv[8] ) );\n\t\t\tdv3.push( sv[6] - ( S2*sv[7] ) );\n\t\t\tdv4.push( sv[5] - ( S3*sv[6] ) );\n\t\t\tdv5.push( sv[4] - ( S4*sv[5] ) );\n\t\t\tdv6.push( sv[3] - ( S5*sv[4] ) );\n\t\t\tdv7.push( sv[2] - ( S6*sv[3] ) );\n\t\t\tdv8.push( sv[1] - ( S7*sv[2] ) );\n\t\t\tdv9.push( sv[0] - ( S8*sv[1] ) );\n\t\t}\n\t} else { // order === 'column-major'\n\t\t// For column-major ndarrays, the first dimensions have the fastest changing indices...\n\t\tS0 = sh[ 0 ];\n\t\tS1 = sh[ 1 ];\n\t\tS2 = sh[ 2 ];\n\t\tS3 = sh[ 3 ];\n\t\tS4 = sh[ 4 ];\n\t\tS5 = sh[ 5 ];\n\t\tS6 = sh[ 6 ];\n\t\tS7 = sh[ 7 ];\n\t\tS8 = sh[ 8 ];\n\t\tS9 = sh[ 9 ];\n\t\tdv0 = [ strides[0] ]; // offset increment for innermost loop\n\t\tdv1 = [ strides[1] - ( S0*strides[0] ) ];\n\t\tdv2 = [ strides[2] - ( S1*strides[1] ) ];\n\t\tdv3 = [ strides[3] - ( S2*strides[2] ) ];\n\t\tdv4 = [ strides[4] - ( S3*strides[3] ) ];\n\t\tdv5 = [ strides[5] - ( S4*strides[4] ) ];\n\t\tdv6 = [ strides[6] - ( S5*strides[5] ) ];\n\t\tdv7 = [ strides[7] - ( S6*strides[6] ) ];\n\t\tdv8 = [ strides[8] - ( S7*strides[7] ) ];\n\t\tdv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop\n\t\tfor ( i = 1; i < arrays.length; i++ ) {\n\t\t\tsv = arrays[ i ].strides;\n\t\t\tdv0.push( sv[0] );\n\t\t\tdv1.push( sv[1] - ( S0*sv[0] ) );\n\t\t\tdv2.push( sv[2] - ( S1*sv[1] ) );\n\t\t\tdv3.push( sv[3] - ( S2*sv[2] ) );\n\t\t\tdv4.push( sv[4] - ( S3*sv[3] ) );\n\t\t\tdv5.push( sv[5] - ( S4*sv[4] ) );\n\t\t\tdv6.push( sv[6] - ( S5*sv[5] ) );\n\t\t\tdv7.push( sv[7] - ( S6*sv[6] ) );\n\t\t\tdv8.push( sv[8] - ( S7*sv[7] ) );\n\t\t\tdv9.push( sv[9] - ( S8*sv[8] ) );\n\t\t}\n\t}\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tiv = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Iterate over the non-reduced ndarray dimensions...\n\tfor ( i9 = 0; i9 < S9; i9++ ) {\n\t\tfor ( i8 = 0; i8 < S8; i8++ ) {\n\t\t\tfor ( i7 = 0; i7 < S7; i7++ ) {\n\t\t\t\tfor ( i6 = 0; i6 < S6; i6++ ) {\n\t\t\t\t\tfor ( i5 = 0; i5 < S5; i5++ ) {\n\t\t\t\t\t\tfor ( i4 = 0; i4 < S4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < S3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < S2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < S1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < S0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t}\n\t\t\tincrementOffsets( iv, dv8 );\n\t\t}\n\t\tincrementOffsets( iv, dv9 );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default unary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9[ k ] = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tybuf[ iv[1] ] = fcn( views, opts );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction blockedunary2d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar ov1;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar j0;\n\tvar j1;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tdv1 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\tif ( j1 < bsize ) {\n\t\t\ts1 = j1;\n\t\t\tj1 = 0;\n\t\t} else {\n\t\t\ts1 = bsize;\n\t\t\tj1 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov1[ k ] = ov[k] + ( j1*sv[k][1] );\n\t\t}\n\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\tif ( j0 < bsize ) {\n\t\t\t\ts0 = j0;\n\t\t\t\tj0 = 0;\n\t\t\t} else {\n\t\t\t\ts0 = bsize;\n\t\t\t\tj0 -= bsize;\n\t\t\t}\n\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t}\n\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t}\n\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary2d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ true, false, true ] ] ]\n*/\nfunction blockedunary3d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar ov1;\n\tvar ov2;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\tif ( j2 < bsize ) {\n\t\t\ts2 = j2;\n\t\t\tj2 = 0;\n\t\t} else {\n\t\t\ts2 = bsize;\n\t\t\tj2 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov2[ k ] = ov[k] + ( j2*sv[k][2] );\n\t\t}\n\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\tif ( j1 < bsize ) {\n\t\t\t\ts1 = j1;\n\t\t\t\tj1 = 0;\n\t\t\t} else {\n\t\t\t\ts1 = bsize;\n\t\t\t\tj1 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t}\n\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\ts0 = j0;\n\t\t\t\t\tj0 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts0 = bsize;\n\t\t\t\t\tj0 -= bsize;\n\t\t\t\t}\n\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t}\n\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t}\n\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary3d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ true, false, true ] ] ] ]\n*/\nfunction blockedunary4d( fcn, arrays, views, strides, opts ) {\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\tif ( j3 < bsize ) {\n\t\t\ts3 = j3;\n\t\t\tj3 = 0;\n\t\t} else {\n\t\t\ts3 = bsize;\n\t\t\tj3 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov3[ k ] = ov[k] + ( j3*sv[k][3] );\n\t\t}\n\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\tif ( j2 < bsize ) {\n\t\t\t\ts2 = j2;\n\t\t\t\tj2 = 0;\n\t\t\t} else {\n\t\t\t\ts2 = bsize;\n\t\t\t\tj2 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t}\n\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\ts1 = j1;\n\t\t\t\t\tj1 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts1 = bsize;\n\t\t\t\t\tj1 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t}\n\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t}\n\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary4d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ true, false, true ] ] ] ] ]\n*/\nfunction blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\tif ( j4 < bsize ) {\n\t\t\ts4 = j4;\n\t\t\tj4 = 0;\n\t\t} else {\n\t\t\ts4 = bsize;\n\t\t\tj4 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov4[ k ] = ov[k] + ( j4*sv[k][4] );\n\t\t}\n\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\tif ( j3 < bsize ) {\n\t\t\t\ts3 = j3;\n\t\t\t\tj3 = 0;\n\t\t\t} else {\n\t\t\t\ts3 = bsize;\n\t\t\t\tj3 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t}\n\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\ts2 = j2;\n\t\t\t\t\tj2 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts2 = bsize;\n\t\t\t\t\tj2 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t}\n\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary5d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ]\n*/\nfunction blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[1];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\tif ( j5 < bsize ) {\n\t\t\ts5 = j5;\n\t\t\tj5 = 0;\n\t\t} else {\n\t\t\ts5 = bsize;\n\t\t\tj5 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov5[ k ] = ov[k] + ( j5*sv[k][5] );\n\t\t}\n\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\tif ( j4 < bsize ) {\n\t\t\t\ts4 = j4;\n\t\t\t\tj4 = 0;\n\t\t\t} else {\n\t\t\t\ts4 = bsize;\n\t\t\t\tj4 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t}\n\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\ts3 = j3;\n\t\t\t\t\tj3 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts3 = bsize;\n\t\t\t\t\tj3 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t}\n\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[1], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary6d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ]\n*/\nfunction blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\tif ( j6 < bsize ) {\n\t\t\ts6 = j6;\n\t\t\tj6 = 0;\n\t\t} else {\n\t\t\ts6 = bsize;\n\t\t\tj6 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov6[ k ] = ov[k] + ( j6*sv[k][6] );\n\t\t}\n\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\tif ( j5 < bsize ) {\n\t\t\t\ts5 = j5;\n\t\t\t\tj5 = 0;\n\t\t\t} else {\n\t\t\t\ts5 = bsize;\n\t\t\t\tj5 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t}\n\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\ts4 = j4;\n\t\t\t\t\tj4 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts4 = bsize;\n\t\t\t\t\tj4 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t}\n\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary7d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\tif ( j7 < bsize ) {\n\t\t\ts7 = j7;\n\t\t\tj7 = 0;\n\t\t} else {\n\t\t\ts7 = bsize;\n\t\t\tj7 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov7[ k ] = ov[k] + ( j7*sv[k][7] );\n\t\t}\n\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\tif ( j6 < bsize ) {\n\t\t\t\ts6 = j6;\n\t\t\t\tj6 = 0;\n\t\t\t} else {\n\t\t\t\ts6 = bsize;\n\t\t\t\tj6 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t}\n\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\ts5 = j5;\n\t\t\t\t\tj5 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts5 = bsize;\n\t\t\t\t\tj5 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t}\n\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary8d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\tif ( j8 < bsize ) {\n\t\t\ts8 = j8;\n\t\t\tj8 = 0;\n\t\t} else {\n\t\t\ts8 = bsize;\n\t\t\tj8 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov8[ k ] = ov[k] + ( j8*sv[k][8] );\n\t\t}\n\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\tif ( j7 < bsize ) {\n\t\t\t\ts7 = j7;\n\t\t\t\tj7 = 0;\n\t\t\t} else {\n\t\t\t\ts7 = bsize;\n\t\t\t\tj7 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t}\n\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\ts6 = j6;\n\t\t\t\t\tj6 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts6 = bsize;\n\t\t\t\t\tj6 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t}\n\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary9d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n/* eslint-disable max-depth, max-len */\n\n'use strict';\n\n// MODULES //\n\nimport loopOrder from '@stdlib/ndarray-base-unary-loop-interchange-order';\nimport blockSize from '@stdlib/ndarray-base-unary-tiling-block-size';\nimport takeIndexed from '@stdlib/array-base-take-indexed';\nimport zeros from '@stdlib/array-base-zeros';\nimport incrementOffsets from './increment_offsets.js';\nimport setViewOffsets from './set_view_offsets.js';\nimport offsets from './offsets.js';\n\n\n// MAIN //\n\n/**\n* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.\n*\n* @private\n* @param {Function} fcn - reduction function\n* @param {Array} arrays - ndarrays\n* @param {Array} views - initialized ndarray-like objects representing sub-array views\n* @param {IntegerArray} strides - loop dimension strides for the input ndarray\n* @param {Options} opts - function options\n* @returns {void}\n*\n* @example\n* import toAccessorArray from '@stdlib/array-base-to-accessor-array';\n* import accessors from '@stdlib/array-base-accessors';\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );\n* var ybuf = toAccessorArray( filled( false, 3 ) );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];\n* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];\n* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major',\n* 'accessors': accessors( xbuf ).accessors\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major',\n* 'accessors': accessors( ybuf ).accessors\n* };\n*\n* // Initialize ndarray-like objects representing sub-array views:\n* var views = [\n* {\n* 'dtype': x.dtype,\n* 'data': x.data,\n* 'shape': [ 2, 2 ],\n* 'strides': [ 2, 1 ],\n* 'offset': x.offset,\n* 'order': x.order\n* }\n* ];\n*\n* // Perform a reduction:\n* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ]\n*/\nfunction blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function\n\tvar bsize;\n\tvar ybuf;\n\tvar set;\n\tvar dv0;\n\tvar dv1;\n\tvar dv2;\n\tvar dv3;\n\tvar dv4;\n\tvar dv5;\n\tvar dv6;\n\tvar dv7;\n\tvar dv8;\n\tvar dv9;\n\tvar ov1;\n\tvar ov2;\n\tvar ov3;\n\tvar ov4;\n\tvar ov5;\n\tvar ov6;\n\tvar ov7;\n\tvar ov8;\n\tvar ov9;\n\tvar sh;\n\tvar s0;\n\tvar s1;\n\tvar s2;\n\tvar s3;\n\tvar s4;\n\tvar s5;\n\tvar s6;\n\tvar s7;\n\tvar s8;\n\tvar s9;\n\tvar sv;\n\tvar ov;\n\tvar iv;\n\tvar i0;\n\tvar i1;\n\tvar i2;\n\tvar i3;\n\tvar i4;\n\tvar i5;\n\tvar i6;\n\tvar i7;\n\tvar i8;\n\tvar i9;\n\tvar j0;\n\tvar j1;\n\tvar j2;\n\tvar j3;\n\tvar j4;\n\tvar j5;\n\tvar j6;\n\tvar j7;\n\tvar j8;\n\tvar j9;\n\tvar N;\n\tvar x;\n\tvar y;\n\tvar o;\n\tvar k;\n\n\t// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...\n\n\tN = arrays.length;\n\tx = arrays[ 0 ];\n\ty = arrays[ 1 ];\n\n\t// Resolve the loop interchange order:\n\to = loopOrder( y.shape, strides, y.strides );\n\tsh = o.sh;\n\tsv = [ o.sx, o.sy ];\n\tfor ( k = 2; k < N; k++ ) {\n\t\tsv.push( takeIndexed( arrays[k].strides, o.idx ) );\n\t}\n\t// Determine the block size:\n\tbsize = blockSize( x.dtype, y.dtype );\n\n\t// Resolve a list of pointers to the first indexed elements in the respective ndarrays:\n\tov = offsets( arrays );\n\n\t// Cache a reference to the output ndarray buffer:\n\tybuf = y.data;\n\n\t// Cache accessors:\n\tset = y.accessors[ 1 ];\n\n\t// Cache offset increments for the innermost loop...\n\tdv0 = [];\n\tfor ( k = 0; k < N; k++ ) {\n\t\tdv0.push( sv[k][0] );\n\t}\n\t// Initialize loop variables...\n\tov1 = zeros( N );\n\tov2 = zeros( N );\n\tov3 = zeros( N );\n\tov4 = zeros( N );\n\tov5 = zeros( N );\n\tov6 = zeros( N );\n\tov7 = zeros( N );\n\tov8 = zeros( N );\n\tov9 = zeros( N );\n\tdv1 = zeros( N );\n\tdv2 = zeros( N );\n\tdv3 = zeros( N );\n\tdv4 = zeros( N );\n\tdv5 = zeros( N );\n\tdv6 = zeros( N );\n\tdv7 = zeros( N );\n\tdv8 = zeros( N );\n\tdv9 = zeros( N );\n\tiv = zeros( N );\n\n\t// Iterate over blocks...\n\tfor ( j9 = sh[9]; j9 > 0; ) {\n\t\tif ( j9 < bsize ) {\n\t\t\ts9 = j9;\n\t\t\tj9 = 0;\n\t\t} else {\n\t\t\ts9 = bsize;\n\t\t\tj9 -= bsize;\n\t\t}\n\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\tov9[ k ] = ov[k] + ( j9*sv[k][9] );\n\t\t}\n\t\tfor ( j8 = sh[8]; j8 > 0; ) {\n\t\t\tif ( j8 < bsize ) {\n\t\t\t\ts8 = j8;\n\t\t\t\tj8 = 0;\n\t\t\t} else {\n\t\t\t\ts8 = bsize;\n\t\t\t\tj8 -= bsize;\n\t\t\t}\n\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\tdv9[ k ] = sv[k][9] - ( s8*sv[k][8] );\n\t\t\t\tov8[ k ] = ov9[k] + ( j8*sv[k][8] );\n\t\t\t}\n\t\t\tfor ( j7 = sh[7]; j7 > 0; ) {\n\t\t\t\tif ( j7 < bsize ) {\n\t\t\t\t\ts7 = j7;\n\t\t\t\t\tj7 = 0;\n\t\t\t\t} else {\n\t\t\t\t\ts7 = bsize;\n\t\t\t\t\tj7 -= bsize;\n\t\t\t\t}\n\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\tdv8[ k ] = sv[k][8] - ( s7*sv[k][7] );\n\t\t\t\t\tov7[ k ] = ov8[k] + ( j7*sv[k][7] );\n\t\t\t\t}\n\t\t\t\tfor ( j6 = sh[6]; j6 > 0; ) {\n\t\t\t\t\tif ( j6 < bsize ) {\n\t\t\t\t\t\ts6 = j6;\n\t\t\t\t\t\tj6 = 0;\n\t\t\t\t\t} else {\n\t\t\t\t\t\ts6 = bsize;\n\t\t\t\t\t\tj6 -= bsize;\n\t\t\t\t\t}\n\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\tdv7[ k ] = sv[k][7] - ( s6*sv[k][6] );\n\t\t\t\t\t\tov6[ k ] = ov7[k] + ( j6*sv[k][6] );\n\t\t\t\t\t}\n\t\t\t\t\tfor ( j5 = sh[5]; j5 > 0; ) {\n\t\t\t\t\t\tif ( j5 < bsize ) {\n\t\t\t\t\t\t\ts5 = j5;\n\t\t\t\t\t\t\tj5 = 0;\n\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\ts5 = bsize;\n\t\t\t\t\t\t\tj5 -= bsize;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\tdv6[ k ] = sv[k][6] - ( s5*sv[k][5] );\n\t\t\t\t\t\t\tov5[ k ] = ov6[k] + ( j5*sv[k][5] );\n\t\t\t\t\t\t}\n\t\t\t\t\t\tfor ( j4 = sh[4]; j4 > 0; ) {\n\t\t\t\t\t\t\tif ( j4 < bsize ) {\n\t\t\t\t\t\t\t\ts4 = j4;\n\t\t\t\t\t\t\t\tj4 = 0;\n\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\ts4 = bsize;\n\t\t\t\t\t\t\t\tj4 -= bsize;\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\tdv5[ k ] = sv[k][5] - ( s4*sv[k][4] );\n\t\t\t\t\t\t\t\tov4[ k ] = ov5[k] + ( j4*sv[k][4] );\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tfor ( j3 = sh[3]; j3 > 0; ) {\n\t\t\t\t\t\t\t\tif ( j3 < bsize ) {\n\t\t\t\t\t\t\t\t\ts3 = j3;\n\t\t\t\t\t\t\t\t\tj3 = 0;\n\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\ts3 = bsize;\n\t\t\t\t\t\t\t\t\tj3 -= bsize;\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\tdv4[ k ] = sv[k][4] - ( s3*sv[k][3] );\n\t\t\t\t\t\t\t\t\tov3[ k ] = ov4[k] + ( j3*sv[k][3] );\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\tfor ( j2 = sh[2]; j2 > 0; ) {\n\t\t\t\t\t\t\t\t\tif ( j2 < bsize ) {\n\t\t\t\t\t\t\t\t\t\ts2 = j2;\n\t\t\t\t\t\t\t\t\t\tj2 = 0;\n\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\ts2 = bsize;\n\t\t\t\t\t\t\t\t\t\tj2 -= bsize;\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\tdv3[ k ] = sv[k][3] - ( s2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t\tov2[ k ] = ov3[k] + ( j2*sv[k][2] );\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\tfor ( j1 = sh[1]; j1 > 0; ) {\n\t\t\t\t\t\t\t\t\t\tif ( j1 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\ts1 = j1;\n\t\t\t\t\t\t\t\t\t\t\tj1 = 0;\n\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\ts1 = bsize;\n\t\t\t\t\t\t\t\t\t\t\tj1 -= bsize;\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\tdv2[ k ] = sv[k][2] - ( s1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t\tov1[ k ] = ov2[k] + ( j1*sv[k][1] );\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\tfor ( j0 = sh[0]; j0 > 0; ) {\n\t\t\t\t\t\t\t\t\t\t\tif ( j0 < bsize ) {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = j0;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 = 0;\n\t\t\t\t\t\t\t\t\t\t\t} else {\n\t\t\t\t\t\t\t\t\t\t\t\ts0 = bsize;\n\t\t\t\t\t\t\t\t\t\t\t\tj0 -= bsize;\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Compute index offsets and loop offset increments for the first ndarray elements in the current block...\n\t\t\t\t\t\t\t\t\t\t\tfor ( k = 0; k < N; k++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tiv[ k ] = ov1[k] + ( j0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t\tdv1[ k ] = sv[k][1] - ( s0*sv[k][0] );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t// Iterate over the non-reduced ndarray dimensions...\n\t\t\t\t\t\t\t\t\t\t\tfor ( i9 = 0; i9 < s9; i9++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\tfor ( i8 = 0; i8 < s8; i8++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i7 = 0; i7 < s7; i7++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i6 = 0; i6 < s6; i6++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i5 = 0; i5 < s5; i5++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i4 = 0; i4 < s4; i4++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i3 = 0; i3 < s3; i3++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i2 = 0; i2 < s2; i2++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i1 = 0; i1 < s1; i1++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tfor ( i0 = 0; i0 < s0; i0++ ) {\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tsetViewOffsets( views, iv );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tset( ybuf, iv[ 1 ], fcn( views, opts ) );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv0 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv1 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv2 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv3 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv4 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv5 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv6 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv7 );\n\t\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv8 );\n\t\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t\t\tincrementOffsets( iv, dv9 );\n\t\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t}\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n}\n\n\n// EXPORTS //\n\nexport default blockedunary10d;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments.\n*\n* ## Notes\n*\n* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively.\n* - This function mutates the provided output array.\n*\n* @private\n* @param {ArrayLikeObject} arrays - list of ndarray-like objects\n* @param {Array} out - output array\n* @returns {Array} output array\n*/\nfunction initializeViews( arrays, out ) {\n\tvar v;\n\tvar i;\n\n\tfor ( i = 2; i < arrays.length; i++ ) {\n\t\tv = arrays[ i ];\n\t\tout.push({\n\t\t\t'dtype': v.dtype,\n\t\t\t'data': v.data,\n\t\t\t'shape': [],\n\t\t\t'strides': [ 0 ],\n\t\t\t'offset': v.offset,\n\t\t\t'order': v.order\n\t\t});\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nexport default initializeViews;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nimport isFunction from '@stdlib/assert-is-function';\nimport format from '@stdlib/error-tools-fmtprodmsg';\nimport reduce from './main.js';\n\n\n// MAIN //\n\n/**\n* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray.\n*\n* @param {Function} fcn - reduction function\n* @throws {TypeError} first argument must be a function\n* @returns {Function} function for performing a reduction\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\nfunction factory( fcn ) {\n\tif ( !isFunction( fcn ) ) {\n\t\tthrow new TypeError( format( 'null3c', fcn ) );\n\t}\n\treturn reducer;\n\n\t/**\n\t* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray.\n\t*\n\t* @private\n\t* @param {ArrayLikeObject} arrays - array-like object containing ndarrays\n\t* @param {IntegerArray} dims - list of dimensions over which to perform a reduction\n\t* @param {Options} [options] - function options\n\t* @returns {void}\n\t*/\n\tfunction reducer( arrays, dims, options ) {\n\t\tvar opts;\n\t\tif ( arguments.length > 2 ) {\n\t\t\topts = options;\n\t\t} else {\n\t\t\topts = {};\n\t\t}\n\t\treturn reduce( fcn, arrays, dims, opts );\n\t}\n}\n\n\n// EXPORTS //\n\nexport default factory;\n","/**\n* @license Apache-2.0\n*\n* Copyright (c) 2025 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n* http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.\n*\n* @module @stdlib/ndarray-base-unary-reduce-subarray\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import every from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Perform a reduction:\n* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*\n* @example\n* import Float64Array from '@stdlib/array-float64';\n* import filled from '@stdlib/array-base-filled';\n* import ndarray2array from '@stdlib/ndarray-base-to-array';\n* import base from '@stdlib/ndarray-base-every';\n* import unaryReduceSubarray from '@stdlib/ndarray-base-unary-reduce-subarray';\n*\n* // Create data buffers:\n* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n* var ybuf = filled( false, 3 );\n*\n* // Define the array shapes:\n* var xsh = [ 1, 3, 2, 2 ];\n* var ysh = [ 1, 3 ];\n*\n* // Define the array strides:\n* var sx = [ 12, 4, 2, 1 ];\n* var sy = [ 3, 1 ];\n*\n* // Define the index offsets:\n* var ox = 0;\n* var oy = 0;\n*\n* // Create an input ndarray-like object:\n* var x = {\n* 'dtype': 'float64',\n* 'data': xbuf,\n* 'shape': xsh,\n* 'strides': sx,\n* 'offset': ox,\n* 'order': 'row-major'\n* };\n*\n* // Create an output ndarray-like object:\n* var y = {\n* 'dtype': 'generic',\n* 'data': ybuf,\n* 'shape': ysh,\n* 'strides': sy,\n* 'offset': oy,\n* 'order': 'row-major'\n* };\n*\n* // Create a function for performing a reduction over subarrays:\n* var every = unaryReduceSubarray.factory( base );\n* // returns \n*\n* // Perform a reduction:\n* every( [ x, y ], [ 2, 3 ] );\n*\n* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );\n* // returns [ [ true, false, true ] ]\n*/\n\n// MODULES //\n\nimport setReadOnly from '@stdlib/utils-define-nonenumerable-read-only-property';\nimport main from './main.js';\nimport factory from './factory.js';\n\n\n// MAIN //\n\nsetReadOnly( main, 'factory', factory );\n\n\n// EXPORTS //\n\nexport default main;\n\n// exports: { \"factory\": \"main.factory\" 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\ No newline at end of file diff --git a/lib/0d.js b/lib/0d.js deleted file mode 100644 index 90f58ee..0000000 --- a/lib/0d.js +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 1 ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data; -* // returns [ true ] -*/ -function unary0d( fcn, arrays, opts ) { - arrays[1].data[ arrays[1].offset ] = fcn( without( arrays, 1 ), opts ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/0d_accessors.js b/lib/0d_accessors.js deleted file mode 100644 index dd7234c..0000000 --- a/lib/0d_accessors.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var without = require( '@stdlib/array-base-without' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 1 ) ); -* -* // Define the array shapes: -* var xsh = [ 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 6, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Perform a reduction: -* unary0d( base, [ x, y ], {} ); -* -* var v = y.data.get( 0 ); -* // returns true -*/ -function unary0d( fcn, arrays, opts ) { - var y = arrays[ 1 ]; - y.accessors[ 1 ]( y.data, y.offset, fcn( without( arrays, 1 ), opts ) ); -} - - -// EXPORTS // - -module.exports = unary0d; diff --git a/lib/10d.js b/lib/10d.js deleted file mode 100644 index fa92d91..0000000 --- a/lib/10d.js +++ /dev/null @@ -1,264 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_accessors.js b/lib/10d_accessors.js deleted file mode 100644 index 3f60306..0000000 --- a/lib/10d_accessors.js +++ /dev/null @@ -1,272 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function unary10d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var S9; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 9 ]; - S1 = sh[ 8 ]; - S2 = sh[ 7 ]; - S3 = sh[ 6 ]; - S4 = sh[ 5 ]; - S5 = sh[ 4 ]; - S6 = sh[ 3 ]; - S7 = sh[ 2 ]; - S8 = sh[ 1 ]; - S9 = sh[ 0 ]; - dv0 = [ strides[9] ]; // offset increment for innermost loop - dv1 = [ strides[8] - ( S0*strides[9] ) ]; - dv2 = [ strides[7] - ( S1*strides[8] ) ]; - dv3 = [ strides[6] - ( S2*strides[7] ) ]; - dv4 = [ strides[5] - ( S3*strides[6] ) ]; - dv5 = [ strides[4] - ( S4*strides[5] ) ]; - dv6 = [ strides[3] - ( S5*strides[4] ) ]; - dv7 = [ strides[2] - ( S6*strides[3] ) ]; - dv8 = [ strides[1] - ( S7*strides[2] ) ]; - dv9 = [ strides[0] - ( S8*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[9] ); - dv1.push( sv[8] - ( S0*sv[9] ) ); - dv2.push( sv[7] - ( S1*sv[8] ) ); - dv3.push( sv[6] - ( S2*sv[7] ) ); - dv4.push( sv[5] - ( S3*sv[6] ) ); - dv5.push( sv[4] - ( S4*sv[5] ) ); - dv6.push( sv[3] - ( S5*sv[4] ) ); - dv7.push( sv[2] - ( S6*sv[3] ) ); - dv8.push( sv[1] - ( S7*sv[2] ) ); - dv9.push( sv[0] - ( S8*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - S9 = sh[ 9 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; - dv9 = [ strides[9] - ( S8*strides[8] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - dv9.push( sv[9] - ( S8*sv[8] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < S9; i9++ ) { - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } -} - - -// EXPORTS // - -module.exports = unary10d; diff --git a/lib/10d_blocked.js b/lib/10d_blocked.js deleted file mode 100644 index 237f221..0000000 --- a/lib/10d_blocked.js +++ /dev/null @@ -1,386 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9[ k ] = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/10d_blocked_accessors.js b/lib/10d_blocked_accessors.js deleted file mode 100644 index 5eb131b..0000000 --- a/lib/10d_blocked_accessors.js +++ /dev/null @@ -1,394 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary10d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] ] -*/ -function blockedunary10d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var dv9; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var ov9; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var s9; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var i9; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var j9; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - ov9 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - dv9 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j9 = sh[9]; j9 > 0; ) { - if ( j9 < bsize ) { - s9 = j9; - j9 = 0; - } else { - s9 = bsize; - j9 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov9[ k ] = ov[k] + ( j9*sv[k][9] ); - } - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv9[ k ] = sv[k][9] - ( s8*sv[k][8] ); - ov8[ k ] = ov9[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i9 = 0; i9 < s9; i9++ ) { - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - incrementOffsets( iv, dv9 ); - } - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary10d; diff --git a/lib/1d.js b/lib/1d.js deleted file mode 100644 index 7da702e..0000000 --- a/lib/1d.js +++ /dev/null @@ -1,140 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/1d_accessors.js b/lib/1d_accessors.js deleted file mode 100644 index f4bba9e..0000000 --- a/lib/1d_accessors.js +++ /dev/null @@ -1,148 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary1d( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unary1d( fcn, arrays, views, strides, opts ) { - var ybuf; - var set; - var dv0; - var sh; - var S0; - var iv; - var i0; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables: dimensions and loop offset (pointer) increments... - S0 = sh[ 0 ]; - dv0 = [ strides[0] ]; - for ( i = 1; i < arrays.length; i++ ) { - dv0.push( arrays[i].strides[0] ); - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } -} - - -// EXPORTS // - -module.exports = unary1d; diff --git a/lib/2d.js b/lib/2d.js deleted file mode 100644 index dade268..0000000 --- a/lib/2d.js +++ /dev/null @@ -1,166 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_accessors.js b/lib/2d_accessors.js deleted file mode 100644 index bc3026d..0000000 --- a/lib/2d_accessors.js +++ /dev/null @@ -1,174 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary2d( base, [ x, y ], views, [ 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function unary2d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var sh; - var S0; - var S1; - var sv; - var iv; - var i0; - var i1; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 1 ]; - S1 = sh[ 0 ]; - dv0 = [ strides[1] ]; // offset increment for innermost loop - dv1 = [ strides[0] - ( S0*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[1] ); - dv1.push( sv[0] - ( S0*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } -} - - -// EXPORTS // - -module.exports = unary2d; diff --git a/lib/2d_blocked.js b/lib/2d_blocked.js deleted file mode 100644 index bad30a0..0000000 --- a/lib/2d_blocked.js +++ /dev/null @@ -1,200 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/2d_blocked_accessors.js b/lib/2d_blocked_accessors.js deleted file mode 100644 index 62dd34b..0000000 --- a/lib/2d_blocked_accessors.js +++ /dev/null @@ -1,208 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function blockedunary2d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var ov1; - var sh; - var s0; - var s1; - var sv; - var ov; - var iv; - var i0; - var i1; - var j0; - var j1; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - dv1 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary2d; diff --git a/lib/3d.js b/lib/3d.js deleted file mode 100644 index a8f6c6e..0000000 --- a/lib/3d.js +++ /dev/null @@ -1,178 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_accessors.js b/lib/3d_accessors.js deleted file mode 100644 index 44fc164..0000000 --- a/lib/3d_accessors.js +++ /dev/null @@ -1,186 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary3d( base, [ x, y ], views, [ 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function unary3d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var sh; - var S0; - var S1; - var S2; - var sv; - var iv; - var i0; - var i1; - var i2; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 2 ]; - S1 = sh[ 1 ]; - S2 = sh[ 0 ]; - dv0 = [ strides[2] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[2] ) ]; - dv2 = [ strides[0] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[2] ); - dv1.push( sv[1] - ( S0*sv[2] ) ); - dv2.push( sv[0] - ( S1*sv[1] ) ); - } - } else { - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } -} - - -// EXPORTS // - -module.exports = unary3d; diff --git a/lib/3d_blocked.js b/lib/3d_blocked.js deleted file mode 100644 index dd9b138..0000000 --- a/lib/3d_blocked.js +++ /dev/null @@ -1,225 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/3d_blocked_accessors.js b/lib/3d_blocked_accessors.js deleted file mode 100644 index 7d91ebe..0000000 --- a/lib/3d_blocked_accessors.js +++ /dev/null @@ -1,233 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary3d( base, [ x, y ], views, [ 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, false, true ] ] ] -*/ -function blockedunary3d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var ov1; - var ov2; - var sh; - var s0; - var s1; - var s2; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var j0; - var j1; - var j2; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary3d; diff --git a/lib/4d.js b/lib/4d.js deleted file mode 100644 index 63d7e9e..0000000 --- a/lib/4d.js +++ /dev/null @@ -1,190 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1]) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_accessors.js b/lib/4d_accessors.js deleted file mode 100644 index c212572..0000000 --- a/lib/4d_accessors.js +++ /dev/null @@ -1,198 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function unary4d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var sh; - var S0; - var S1; - var S2; - var S3; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 3 ]; - S1 = sh[ 2 ]; - S2 = sh[ 1 ]; - S3 = sh[ 0 ]; - dv0 = [ strides[3] ]; // offset increment for innermost loop - dv1 = [ strides[2] - ( S0*strides[3] ) ]; - dv2 = [ strides[1] - ( S1*strides[2] ) ]; - dv3 = [ strides[0] - ( S2*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[3] ); - dv1.push( sv[2] - ( S0*sv[3] ) ); - dv2.push( sv[1] - ( S1*sv[2] ) ); - dv3.push( sv[0] - ( S2*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2]) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } -} - - -// EXPORTS // - -module.exports = unary4d; diff --git a/lib/4d_blocked.js b/lib/4d_blocked.js deleted file mode 100644 index 2d773bd..0000000 --- a/lib/4d_blocked.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/4d_blocked_accessors.js b/lib/4d_blocked_accessors.js deleted file mode 100644 index 31ec273..0000000 --- a/lib/4d_blocked_accessors.js +++ /dev/null @@ -1,256 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary4d( base, [ x, y ], views, [ 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ true, false, true ] ] ] ] -*/ -function blockedunary4d( fcn, arrays, views, strides, opts ) { - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var ov1; - var ov2; - var ov3; - var sh; - var s0; - var s1; - var s2; - var s3; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var j0; - var j1; - var j2; - var j3; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov3[ k ] = ov[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary4d; diff --git a/lib/5d.js b/lib/5d.js deleted file mode 100644 index 9c7e7aa..0000000 --- a/lib/5d.js +++ /dev/null @@ -1,202 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_accessors.js b/lib/5d_accessors.js deleted file mode 100644 index fe9a796..0000000 --- a/lib/5d_accessors.js +++ /dev/null @@ -1,210 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function unary5d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 4 ]; - S1 = sh[ 3 ]; - S2 = sh[ 2 ]; - S3 = sh[ 1 ]; - S4 = sh[ 0 ]; - dv0 = [ strides[4] ]; // offset increment for innermost loop - dv1 = [ strides[3] - ( S0*strides[4] ) ]; - dv2 = [ strides[2] - ( S1*strides[3] ) ]; - dv3 = [ strides[1] - ( S2*strides[2] ) ]; - dv4 = [ strides[0] - ( S3*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[4] ); - dv1.push( sv[3] - ( S0*sv[4] ) ); - dv2.push( sv[2] - ( S1*sv[3] ) ); - dv3.push( sv[1] - ( S2*sv[2] ) ); - dv4.push( sv[0] - ( S3*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } -} - - -// EXPORTS // - -module.exports = unary5d; diff --git a/lib/5d_blocked.js b/lib/5d_blocked.js deleted file mode 100644 index 4c1f66d..0000000 --- a/lib/5d_blocked.js +++ /dev/null @@ -1,271 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/5d_blocked_accessors.js b/lib/5d_blocked_accessors.js deleted file mode 100644 index 7e50eb6..0000000 --- a/lib/5d_blocked_accessors.js +++ /dev/null @@ -1,279 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary5d( base, [ x, y ], views, [ 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ true, false, true ] ] ] ] ] -*/ -function blockedunary5d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var ov1; - var ov2; - var ov3; - var ov4; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var j0; - var j1; - var j2; - var j3; - var j4; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov4[ k ] = ov[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary5d; diff --git a/lib/6d.js b/lib/6d.js deleted file mode 100644 index a296861..0000000 --- a/lib/6d.js +++ /dev/null @@ -1,216 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_accessors.js b/lib/6d_accessors.js deleted file mode 100644 index cafbe6e..0000000 --- a/lib/6d_accessors.js +++ /dev/null @@ -1,224 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function unary6d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 5 ]; - S1 = sh[ 4 ]; - S2 = sh[ 3 ]; - S3 = sh[ 2 ]; - S4 = sh[ 1 ]; - S5 = sh[ 0 ]; - dv0 = [ strides[5] ]; // offset increment for innermost loop - dv1 = [ strides[4] - ( S0*strides[5] ) ]; - dv2 = [ strides[3] - ( S1*strides[4] ) ]; - dv3 = [ strides[2] - ( S2*strides[3] ) ]; - dv4 = [ strides[1] - ( S3*strides[2] ) ]; - dv5 = [ strides[0] - ( S4*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[5] ); - dv1.push( sv[4] - ( S0*sv[5] ) ); - dv2.push( sv[3] - ( S1*sv[4] ) ); - dv3.push( sv[2] - ( S2*sv[3] ) ); - dv4.push( sv[1] - ( S3*sv[2] ) ); - dv5.push( sv[0] - ( S4*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } -} - - -// EXPORTS // - -module.exports = unary6d; diff --git a/lib/6d_blocked.js b/lib/6d_blocked.js deleted file mode 100644 index f11bfe8..0000000 --- a/lib/6d_blocked.js +++ /dev/null @@ -1,294 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/6d_blocked_accessors.js b/lib/6d_blocked_accessors.js deleted file mode 100644 index 9acf3c2..0000000 --- a/lib/6d_blocked_accessors.js +++ /dev/null @@ -1,302 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary6d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ true, false, true ] ] ] ] ] ] -*/ -function blockedunary6d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[1]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov5[ k ] = ov[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[1], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary6d; diff --git a/lib/7d.js b/lib/7d.js deleted file mode 100644 index 87df811..0000000 --- a/lib/7d.js +++ /dev/null @@ -1,228 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_accessors.js b/lib/7d_accessors.js deleted file mode 100644 index 468524a..0000000 --- a/lib/7d_accessors.js +++ /dev/null @@ -1,236 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function unary7d( fcn, arrays, views, strides, isRowMajor, opts ) { - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 6 ]; - S1 = sh[ 5 ]; - S2 = sh[ 4 ]; - S3 = sh[ 3 ]; - S4 = sh[ 2 ]; - S5 = sh[ 1 ]; - S6 = sh[ 0 ]; - dv0 = [ strides[6] ]; // offset increment for innermost loop - dv1 = [ strides[5] - ( S0*strides[6] ) ]; - dv2 = [ strides[4] - ( S1*strides[5] ) ]; - dv3 = [ strides[3] - ( S2*strides[4] ) ]; - dv4 = [ strides[2] - ( S3*strides[3] ) ]; - dv5 = [ strides[1] - ( S4*strides[2] ) ]; - dv6 = [ strides[0] - ( S5*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[6] ); - dv1.push( sv[5] - ( S0*sv[6] ) ); - dv2.push( sv[4] - ( S1*sv[5] ) ); - dv3.push( sv[3] - ( S2*sv[4] ) ); - dv4.push( sv[2] - ( S3*sv[3] ) ); - dv5.push( sv[1] - ( S4*sv[2] ) ); - dv6.push( sv[0] - ( S5*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } -} - - -// EXPORTS // - -module.exports = unary7d; diff --git a/lib/7d_blocked.js b/lib/7d_blocked.js deleted file mode 100644 index 1e63eb6..0000000 --- a/lib/7d_blocked.js +++ /dev/null @@ -1,317 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/7d_blocked_accessors.js b/lib/7d_blocked_accessors.js deleted file mode 100644 index e60375e..0000000 --- a/lib/7d_blocked_accessors.js +++ /dev/null @@ -1,325 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary7d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] -*/ -function blockedunary7d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov6[ k ] = ov[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary7d; diff --git a/lib/8d.js b/lib/8d.js deleted file mode 100644 index 35ec78a..0000000 --- a/lib/8d.js +++ /dev/null @@ -1,240 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_accessors.js b/lib/8d_accessors.js deleted file mode 100644 index 8d18558..0000000 --- a/lib/8d_accessors.js +++ /dev/null @@ -1,248 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function unary8d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 7 ]; - S1 = sh[ 6 ]; - S2 = sh[ 5 ]; - S3 = sh[ 4 ]; - S4 = sh[ 3 ]; - S5 = sh[ 2 ]; - S6 = sh[ 1 ]; - S7 = sh[ 0 ]; - dv0 = [ strides[7] ]; // offset increment for innermost loop - dv1 = [ strides[6] - ( S0*strides[7] ) ]; - dv2 = [ strides[5] - ( S1*strides[6] ) ]; - dv3 = [ strides[4] - ( S2*strides[5] ) ]; - dv4 = [ strides[3] - ( S3*strides[4] ) ]; - dv5 = [ strides[2] - ( S4*strides[3] ) ]; - dv6 = [ strides[1] - ( S5*strides[2] ) ]; - dv7 = [ strides[0] - ( S6*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[7] ); - dv1.push( sv[6] - ( S0*sv[7] ) ); - dv2.push( sv[5] - ( S1*sv[6] ) ); - dv3.push( sv[4] - ( S2*sv[5] ) ); - dv4.push( sv[3] - ( S3*sv[4] ) ); - dv5.push( sv[2] - ( S4*sv[3] ) ); - dv6.push( sv[1] - ( S5*sv[2] ) ); - dv7.push( sv[0] - ( S6*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } -} - - -// EXPORTS // - -module.exports = unary8d; diff --git a/lib/8d_blocked.js b/lib/8d_blocked.js deleted file mode 100644 index cb21b57..0000000 --- a/lib/8d_blocked.js +++ /dev/null @@ -1,340 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/8d_blocked_accessors.js b/lib/8d_blocked_accessors.js deleted file mode 100644 index d868c12..0000000 --- a/lib/8d_blocked_accessors.js +++ /dev/null @@ -1,348 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary8d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] -*/ -function blockedunary8d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov7[ k ] = ov[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary8d; diff --git a/lib/9d.js b/lib/9d.js deleted file mode 100644 index 14509e8..0000000 --- a/lib/9d.js +++ /dev/null @@ -1,252 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_accessors.js b/lib/9d_accessors.js deleted file mode 100644 index 355ed51..0000000 --- a/lib/9d_accessors.js +++ /dev/null @@ -1,260 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {boolean} isRowMajor - boolean indicating if provided arrays are in row-major order -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], true, {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function unary9d( fcn, arrays, views, strides, isRowMajor, opts ) { // eslint-disable-line max-statements - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var sh; - var S0; - var S1; - var S2; - var S3; - var S4; - var S5; - var S6; - var S7; - var S8; - var sv; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var y; - var i; - - // Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop... - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... - if ( isRowMajor ) { - // For row-major ndarrays, the last dimensions have the fastest changing indices... - S0 = sh[ 8 ]; - S1 = sh[ 7 ]; - S2 = sh[ 6 ]; - S3 = sh[ 5 ]; - S4 = sh[ 4 ]; - S5 = sh[ 3 ]; - S6 = sh[ 2 ]; - S7 = sh[ 1 ]; - S8 = sh[ 0 ]; - dv0 = [ strides[8] ]; // offset increment for innermost loop - dv1 = [ strides[7] - ( S0*strides[8] ) ]; - dv2 = [ strides[6] - ( S1*strides[7] ) ]; - dv3 = [ strides[5] - ( S2*strides[6] ) ]; - dv4 = [ strides[4] - ( S3*strides[5] ) ]; - dv5 = [ strides[3] - ( S4*strides[4] ) ]; - dv6 = [ strides[2] - ( S5*strides[3] ) ]; - dv7 = [ strides[1] - ( S6*strides[2] ) ]; - dv8 = [ strides[0] - ( S7*strides[1] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[8] ); - dv1.push( sv[7] - ( S0*sv[8] ) ); - dv2.push( sv[6] - ( S1*sv[7] ) ); - dv3.push( sv[5] - ( S2*sv[6] ) ); - dv4.push( sv[4] - ( S3*sv[5] ) ); - dv5.push( sv[3] - ( S4*sv[4] ) ); - dv6.push( sv[2] - ( S5*sv[3] ) ); - dv7.push( sv[1] - ( S6*sv[2] ) ); - dv8.push( sv[0] - ( S7*sv[1] ) ); - } - } else { // order === 'column-major' - // For column-major ndarrays, the first dimensions have the fastest changing indices... - S0 = sh[ 0 ]; - S1 = sh[ 1 ]; - S2 = sh[ 2 ]; - S3 = sh[ 3 ]; - S4 = sh[ 4 ]; - S5 = sh[ 5 ]; - S6 = sh[ 6 ]; - S7 = sh[ 7 ]; - S8 = sh[ 8 ]; - dv0 = [ strides[0] ]; // offset increment for innermost loop - dv1 = [ strides[1] - ( S0*strides[0] ) ]; - dv2 = [ strides[2] - ( S1*strides[1] ) ]; - dv3 = [ strides[3] - ( S2*strides[2] ) ]; - dv4 = [ strides[4] - ( S3*strides[3] ) ]; - dv5 = [ strides[5] - ( S4*strides[4] ) ]; - dv6 = [ strides[6] - ( S5*strides[5] ) ]; - dv7 = [ strides[7] - ( S6*strides[6] ) ]; - dv8 = [ strides[8] - ( S7*strides[7] ) ]; // offset increment for outermost loop - for ( i = 1; i < arrays.length; i++ ) { - sv = arrays[ i ].strides; - dv0.push( sv[0] ); - dv1.push( sv[1] - ( S0*sv[0] ) ); - dv2.push( sv[2] - ( S1*sv[1] ) ); - dv3.push( sv[3] - ( S2*sv[2] ) ); - dv4.push( sv[4] - ( S3*sv[3] ) ); - dv5.push( sv[5] - ( S4*sv[4] ) ); - dv6.push( sv[6] - ( S5*sv[5] ) ); - dv7.push( sv[7] - ( S6*sv[6] ) ); - dv8.push( sv[8] - ( S7*sv[7] ) ); - } - } - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < S8; i8++ ) { - for ( i7 = 0; i7 < S7; i7++ ) { - for ( i6 = 0; i6 < S6; i6++ ) { - for ( i5 = 0; i5 < S5; i5++ ) { - for ( i4 = 0; i4 < S4; i4++ ) { - for ( i3 = 0; i3 < S3; i3++ ) { - for ( i2 = 0; i2 < S2; i2++ ) { - for ( i1 = 0; i1 < S1; i1++ ) { - for ( i0 = 0; i0 < S0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } -} - - -// EXPORTS // - -module.exports = unary9d; diff --git a/lib/9d_blocked.js b/lib/9d_blocked.js deleted file mode 100644 index fd076cd..0000000 --- a/lib/9d_blocked.js +++ /dev/null @@ -1,363 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - ybuf[ iv[1] ] = fcn( views, opts ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/9d_blocked_accessors.js b/lib/9d_blocked_accessors.js deleted file mode 100644 index 6471aa1..0000000 --- a/lib/9d_blocked_accessors.js +++ /dev/null @@ -1,371 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable max-depth, max-len */ - -'use strict'; - -// MODULES // - -var loopOrder = require( '@stdlib/ndarray-base-unary-loop-interchange-order' ); -var blockSize = require( '@stdlib/ndarray-base-unary-tiling-block-size' ); -var takeIndexed = require( '@stdlib/array-base-take-indexed' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var incrementOffsets = require( './increment_offsets.js' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ]; -* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ]; -* var sy = [ 3, 3, 3, 3, 3, 3, 3, 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* blockedunary9d( base, [ x, y ], views, [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ [ [ [ [ [ [ true, false, true ] ] ] ] ] ] ] ] ] -*/ -function blockedunary9d( fcn, arrays, views, strides, opts ) { // eslint-disable-line max-statements, max-lines-per-function - var bsize; - var ybuf; - var set; - var dv0; - var dv1; - var dv2; - var dv3; - var dv4; - var dv5; - var dv6; - var dv7; - var dv8; - var ov1; - var ov2; - var ov3; - var ov4; - var ov5; - var ov6; - var ov7; - var ov8; - var sh; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var s8; - var sv; - var ov; - var iv; - var i0; - var i1; - var i2; - var i3; - var i4; - var i5; - var i6; - var i7; - var i8; - var j0; - var j1; - var j2; - var j3; - var j4; - var j5; - var j6; - var j7; - var j8; - var N; - var x; - var y; - var o; - var k; - - // Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... - - N = arrays.length; - x = arrays[ 0 ]; - y = arrays[ 1 ]; - - // Resolve the loop interchange order: - o = loopOrder( y.shape, strides, y.strides ); - sh = o.sh; - sv = [ o.sx, o.sy ]; - for ( k = 2; k < N; k++ ) { - sv.push( takeIndexed( arrays[k].strides, o.idx ) ); - } - // Determine the block size: - bsize = blockSize( x.dtype, y.dtype ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - ov = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Cache offset increments for the innermost loop... - dv0 = []; - for ( k = 0; k < N; k++ ) { - dv0.push( sv[k][0] ); - } - // Initialize loop variables... - ov1 = zeros( N ); - ov2 = zeros( N ); - ov3 = zeros( N ); - ov4 = zeros( N ); - ov5 = zeros( N ); - ov6 = zeros( N ); - ov7 = zeros( N ); - ov8 = zeros( N ); - dv1 = zeros( N ); - dv2 = zeros( N ); - dv3 = zeros( N ); - dv4 = zeros( N ); - dv5 = zeros( N ); - dv6 = zeros( N ); - dv7 = zeros( N ); - dv8 = zeros( N ); - iv = zeros( N ); - - // Iterate over blocks... - for ( j8 = sh[8]; j8 > 0; ) { - if ( j8 < bsize ) { - s8 = j8; - j8 = 0; - } else { - s8 = bsize; - j8 -= bsize; - } - for ( k = 0; k < N; k++ ) { - ov8[ k ] = ov[k] + ( j8*sv[k][8] ); - } - for ( j7 = sh[7]; j7 > 0; ) { - if ( j7 < bsize ) { - s7 = j7; - j7 = 0; - } else { - s7 = bsize; - j7 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv8[ k ] = sv[k][8] - ( s7*sv[k][7] ); - ov7[ k ] = ov8[k] + ( j7*sv[k][7] ); - } - for ( j6 = sh[6]; j6 > 0; ) { - if ( j6 < bsize ) { - s6 = j6; - j6 = 0; - } else { - s6 = bsize; - j6 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv7[ k ] = sv[k][7] - ( s6*sv[k][6] ); - ov6[ k ] = ov7[k] + ( j6*sv[k][6] ); - } - for ( j5 = sh[5]; j5 > 0; ) { - if ( j5 < bsize ) { - s5 = j5; - j5 = 0; - } else { - s5 = bsize; - j5 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv6[ k ] = sv[k][6] - ( s5*sv[k][5] ); - ov5[ k ] = ov6[k] + ( j5*sv[k][5] ); - } - for ( j4 = sh[4]; j4 > 0; ) { - if ( j4 < bsize ) { - s4 = j4; - j4 = 0; - } else { - s4 = bsize; - j4 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv5[ k ] = sv[k][5] - ( s4*sv[k][4] ); - ov4[ k ] = ov5[k] + ( j4*sv[k][4] ); - } - for ( j3 = sh[3]; j3 > 0; ) { - if ( j3 < bsize ) { - s3 = j3; - j3 = 0; - } else { - s3 = bsize; - j3 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv4[ k ] = sv[k][4] - ( s3*sv[k][3] ); - ov3[ k ] = ov4[k] + ( j3*sv[k][3] ); - } - for ( j2 = sh[2]; j2 > 0; ) { - if ( j2 < bsize ) { - s2 = j2; - j2 = 0; - } else { - s2 = bsize; - j2 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv3[ k ] = sv[k][3] - ( s2*sv[k][2] ); - ov2[ k ] = ov3[k] + ( j2*sv[k][2] ); - } - for ( j1 = sh[1]; j1 > 0; ) { - if ( j1 < bsize ) { - s1 = j1; - j1 = 0; - } else { - s1 = bsize; - j1 -= bsize; - } - for ( k = 0; k < N; k++ ) { - dv2[ k ] = sv[k][2] - ( s1*sv[k][1] ); - ov1[ k ] = ov2[k] + ( j1*sv[k][1] ); - } - for ( j0 = sh[0]; j0 > 0; ) { - if ( j0 < bsize ) { - s0 = j0; - j0 = 0; - } else { - s0 = bsize; - j0 -= bsize; - } - // Compute index offsets and loop offset increments for the first ndarray elements in the current block... - for ( k = 0; k < N; k++ ) { - iv[ k ] = ov1[k] + ( j0*sv[k][0] ); - dv1[ k ] = sv[k][1] - ( s0*sv[k][0] ); - } - // Iterate over the non-reduced ndarray dimensions... - for ( i8 = 0; i8 < s8; i8++ ) { - for ( i7 = 0; i7 < s7; i7++ ) { - for ( i6 = 0; i6 < s6; i6++ ) { - for ( i5 = 0; i5 < s5; i5++ ) { - for ( i4 = 0; i4 < s4; i4++ ) { - for ( i3 = 0; i3 < s3; i3++ ) { - for ( i2 = 0; i2 < s2; i2++ ) { - for ( i1 = 0; i1 < s1; i1++ ) { - for ( i0 = 0; i0 < s0; i0++ ) { - setViewOffsets( views, iv ); - set( ybuf, iv[ 1 ], fcn( views, opts ) ); - incrementOffsets( iv, dv0 ); - } - incrementOffsets( iv, dv1 ); - } - incrementOffsets( iv, dv2 ); - } - incrementOffsets( iv, dv3 ); - } - incrementOffsets( iv, dv4 ); - } - incrementOffsets( iv, dv5 ); - } - incrementOffsets( iv, dv6 ); - } - incrementOffsets( iv, dv7 ); - } - incrementOffsets( iv, dv8 ); - } - } - } - } - } - } - } - } - } - } -} - - -// EXPORTS // - -module.exports = blockedunary9d; diff --git a/lib/factory.js b/lib/factory.js deleted file mode 100644 index 99cb1ac..0000000 --- a/lib/factory.js +++ /dev/null @@ -1,118 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isFunction = require( '@stdlib/assert-is-function' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var reduce = require( './main.js' ); - - -// MAIN // - -/** -* Returns a function for performing a reduction over a list of specified dimensions in an input ndarray and assigning results to a provided output ndarray. -* -* @param {Function} fcn - reduction function -* @throws {TypeError} first argument must be a function -* @returns {Function} function for performing a reduction -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ -function factory( fcn ) { - if ( !isFunction( fcn ) ) { - throw new TypeError( format( 'null3c', fcn ) ); - } - return reducer; - - /** - * Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. - * - * @private - * @param {ArrayLikeObject} arrays - array-like object containing ndarrays - * @param {IntegerArray} dims - list of dimensions over which to perform a reduction - * @param {Options} [options] - function options - * @returns {void} - */ - function reducer( arrays, dims, options ) { - var opts; - if ( arguments.length > 2 ) { - opts = options; - } else { - opts = {}; - } - return reduce( fcn, arrays, dims, opts ); - } -} - - -// EXPORTS // - -module.exports = factory; diff --git a/lib/increment_offsets.js b/lib/increment_offsets.js deleted file mode 100644 index 7d52552..0000000 --- a/lib/increment_offsets.js +++ /dev/null @@ -1,46 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Increments index offsets according to a list of increments. -* -* ## Notes -* -* - This function mutates the list of index offsets. -* -* @private -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @param {NonNegativeIntegerArray} inc - list of increments -* @returns {NonNegativeIntegerArray} updated offsets -*/ -function incrementOffsets( offsets, inc ) { - var i; - for ( i = 0; i < offsets.length; i++ ) { - offsets[ i ] += inc[ i ]; - } - return offsets; -} - - -// EXPORTS // - -module.exports = incrementOffsets; diff --git a/lib/index.js b/lib/index.js deleted file mode 100644 index bd5a592..0000000 --- a/lib/index.js +++ /dev/null @@ -1,145 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray. -* -* @module @stdlib/ndarray-base-unary-reduce-subarray -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Create a function for performing a reduction over subarrays: -* var every = unaryReduceSubarray.factory( base ); -* // returns -* -* // Perform a reduction: -* every( [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -*/ - -// MODULES // - -var setReadOnly = require( '@stdlib/utils-define-nonenumerable-read-only-property' ); -var main = require( './main.js' ); -var factory = require( './factory.js' ); - - -// MAIN // - -setReadOnly( main, 'factory', factory ); - - -// EXPORTS // - -module.exports = main; - -// exports: { "factory": "main.factory" } diff --git a/lib/initialize_array_views.js b/lib/initialize_array_views.js deleted file mode 100644 index f9f5225..0000000 --- a/lib/initialize_array_views.js +++ /dev/null @@ -1,57 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Initialize ndarray-like objects for representing zero-dimensional sub-array views of ancillary ndarray arguments. -* -* ## Notes -* -* - This function ignores the first two ndarray-like objects, which are assumed to be the input and output ndarray, respectively. -* - This function mutates the provided output array. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @param {Array} out - output array -* @returns {Array} output array -*/ -function initializeViews( arrays, out ) { - var v; - var i; - - for ( i = 2; i < arrays.length; i++ ) { - v = arrays[ i ]; - out.push({ - 'dtype': v.dtype, - 'data': v.data, - 'shape': [], - 'strides': [ 0 ], - 'offset': v.offset, - 'order': v.order - }); - } - return out; -} - - -// EXPORTS // - -module.exports = initializeViews; diff --git a/lib/main.js b/lib/main.js deleted file mode 100644 index 80bbe42..0000000 --- a/lib/main.js +++ /dev/null @@ -1,469 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var ndarray2object = require( '@stdlib/ndarray-base-ndarraylike2object' ); -var normalizeIndices = require( '@stdlib/ndarray-base-to-unique-normalized-indices' ); -var indicesComplement = require( '@stdlib/array-base-indices-complement' ); -var takeIndexed2 = require( '@stdlib/array-base-take-indexed2' ); -var iterationOrder = require( '@stdlib/ndarray-base-iteration-order' ); -var strides2order = require( '@stdlib/ndarray-base-strides2order' ); -var numel = require( '@stdlib/ndarray-base-numel' ); -var join = require( '@stdlib/array-base-join' ); -var format = require( '@stdlib/error-tools-fmtprodmsg' ); -var initializeViews = require( './initialize_array_views.js' ); -var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); -var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); -var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); -var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); -var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); -var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); -var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); -var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); -var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); -var blockedunary2d = require( './2d_blocked.js' ); -var blockedunary3d = require( './3d_blocked.js' ); -var blockedunary4d = require( './4d_blocked.js' ); -var blockedunary5d = require( './5d_blocked.js' ); -var blockedunary6d = require( './6d_blocked.js' ); -var blockedunary7d = require( './7d_blocked.js' ); -var blockedunary8d = require( './8d_blocked.js' ); -var blockedunary9d = require( './9d_blocked.js' ); -var blockedunary10d = require( './10d_blocked.js' ); -var accessorunary0d = require( './0d_accessors.js' ); -var accessorunary1d = require( './1d_accessors.js' ); -var accessorunary2d = require( './2d_accessors.js' ); -var accessorunary3d = require( './3d_accessors.js' ); -var accessorunary4d = require( './4d_accessors.js' ); -var accessorunary5d = require( './5d_accessors.js' ); -var accessorunary6d = require( './6d_accessors.js' ); -var accessorunary7d = require( './7d_accessors.js' ); -var accessorunary8d = require( './8d_accessors.js' ); -var accessorunary9d = require( './9d_accessors.js' ); -var accessorunary10d = require( './10d_accessors.js' ); -var accessorunarynd = require( './nd_accessors.js' ); -var unary0d = require( './0d.js' ); -var unary1d = require( './1d.js' ); -var unary2d = require( './2d.js' ); -var unary3d = require( './3d.js' ); -var unary4d = require( './4d.js' ); -var unary5d = require( './5d.js' ); -var unary6d = require( './6d.js' ); -var unary7d = require( './7d.js' ); -var unary8d = require( './8d.js' ); -var unary9d = require( './9d.js' ); -var unary10d = require( './10d.js' ); -var unarynd = require( './nd.js' ); - - -// VARIABLES // - -var UNARY = [ - unary0d, - unary1d, - unary2d, - unary3d, - unary4d, - unary5d, - unary6d, - unary7d, - unary8d, - unary9d, - unary10d -]; -var ACCESSOR_UNARY = [ - accessorunary0d, - accessorunary1d, - accessorunary2d, - accessorunary3d, - accessorunary4d, - accessorunary5d, - accessorunary6d, - accessorunary7d, - accessorunary8d, - accessorunary9d, - accessorunary10d -]; -var BLOCKED_UNARY = [ - blockedunary2d, // 0 - blockedunary3d, - blockedunary4d, - blockedunary5d, - blockedunary6d, - blockedunary7d, - blockedunary8d, - blockedunary9d, - blockedunary10d // 8 -]; -var BLOCKED_ACCESSOR_UNARY = [ - blockedaccessorunary2d, // 0 - blockedaccessorunary3d, - blockedaccessorunary4d, - blockedaccessorunary5d, - blockedaccessorunary6d, - blockedaccessorunary7d, - blockedaccessorunary8d, - blockedaccessorunary9d, - blockedaccessorunary10d // 8 -]; -var MAX_DIMS = UNARY.length - 1; - - -// MAIN // - -/** -* Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @param {IntegerArray} dims - list of dimensions over which to perform a reduction -* @param {Options} [options] - function options -* @throws {Error} arrays must have the expected number of dimensions -* @throws {RangeError} dimension indices must not exceed input ndarray bounds -* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions -* @throws {Error} must provide unique dimension indices -* @throws {Error} arrays must have the same loop dimension sizes -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = [ 1, 3 ]; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 3, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ true, false, true ] ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = [ false ]; -* -* // Define the array shapes: -* var xsh = [ 1, 3, 2, 2 ]; -* var ysh = []; -* -* // Define the array strides: -* var sx = [ 12, 4, 2, 1 ]; -* var sy = [ 0 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [ 0, 1, 2, 3 ] ); -* -* var v = y.data; -* // returns [ true ] -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var every = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 12 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3, 2, 2 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 4, 2, 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Perform a reduction: -* unaryReduceSubarray( every, [ x, y ], [] ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ [ [ true, true ], [ true, true ] ], [ [ true, false ], [ true, true ] ], [ [ true, true ], [ true, true ] ] ] -*/ -function unaryReduceSubarray( fcn, arrays, dims, options ) { // eslint-disable-line max-statements - var views; - var ndims; - var ldims; - var opts; - var arr; - var tmp; - var len; - var shx; - var shc; - var shl; - var iox; - var ioy; - var ord; - var sc; - var sl; - var sy; - var ns; - var d; - var s; - var N; - var M; - var K; - var x; - var y; - var i; - var j; - - if ( arguments.length > 3 ) { - opts = options; - } else { - opts = {}; - } - // Standardize ndarray meta data... - N = arrays.length; - arr = []; - for ( i = 0; i < N; i++ ) { - arr.push( ndarray2object( arrays[ i ] ) ); - } - // Cache references to the input and output arrays: - x = arr[ 0 ]; - y = arr[ 1 ]; - - // Resolve the number of input array dimensions: - shx = x.shape; - ndims = shx.length; - - // Verify that we've been provided a list of unique dimension indices... - M = dims.length; - d = normalizeIndices( dims, ndims-1 ); - if ( d === null ) { - throw new RangeError( format( 'invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].', join( dims, ',' ) ) ); - } - d.sort(); - if ( d.length !== M ) { - throw new Error( format( 'invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].', join( dims, ',' ) ) ); - } - // Check whether we've been provided a valid number of dimensions to reduce... - if ( M > ndims ) { - throw new RangeError( format( 'invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].', ndims, join( dims, ',' ) ) ); - } - // Verify that provided ndarrays have the expected number of dimensions... - K = ndims - M; - for ( i = 1; i < N; i++ ) { - if ( arr[ i ].shape.length !== K ) { - throw new Error( format( 'invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).', join( shx, ',' ), K, join( arr[ i ].shape, ',' ), i ) ); - } - } - // Determine whether we can avoid iteration altogether... - if ( K === 0 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, opts ); - } - return UNARY[ K ]( fcn, arr, opts ); - } - // Resolve the non-reduced ("loop") dimensions and associated strides: - ldims = indicesComplement( shx.length, d ); - tmp = takeIndexed2( shx, x.strides, ldims ); - shl = tmp[ 0 ]; - sl = tmp[ 1 ]; - - // Resolve the reduced ("core") dimensions and associated strides: - tmp = takeIndexed2( shx, x.strides, d ); - shc = tmp[ 0 ]; - sc = tmp[ 1 ]; - - // Verify that the provided arrays have the same loop dimensions... - len = 1; // number of elements - ns = 0; // number of singleton dimensions - for ( i = 0; i < K; i++ ) { - s = shl[ i ]; - for ( j = 1; j < N; j++ ) { - if ( s !== arr[ j ].shape[ i ] ) { - throw new Error( format( 'invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).', join( shx, ',' ), join( ldims, ',' ), join( shl, ',' ), join( arr[ j ].shape, ',' ), j ) ); - } - } - // Note that, if one of the dimensions is `0`, the length will be `0`... - len *= s; - - // Check whether the current dimension is a singleton dimension... - if ( s === 1 ) { - ns += 1; - } - } - // Check whether we were provided empty ndarrays... - if ( len === 0 || ( shc.length && numel( shc ) === 0 ) ) { - return; - } - // Initialize ndarray-like objects for representing sub-array views... - views = [ - { - 'dtype': x.dtype, - 'data': x.data, - 'shape': shc, - 'strides': sc, - 'offset': x.offset, - 'order': x.order - } - ]; - initializeViews( arr, views ); - - // Determine whether we only have one loop dimension and can thus readily perform one-dimensional iteration... - if ( K === 1 ) { - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, opts ); - } - sy = y.strides; - - // Determine whether the loop dimensions have only **one** non-singleton dimension (e.g., shape=[10,1,1,1]) so that we can treat loop iteration as being equivalent to one-dimensional iteration... - if ( ns === K-1 ) { - // Get the index of the non-singleton dimension... - for ( i = 0; i < K; i++ ) { - if ( shl[ i ] !== 1 ) { - break; - } - } - y.shape = [ shl[i] ]; - for ( j = 0; j < N; j++ ) { - arr[ j ].strides = [ arr[j].strides[i] ]; - } - sl = [ sl[i] ]; - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - return UNARY[ 1 ]( fcn, arr, views, sl, opts ); - } - iox = iterationOrder( sl ); // +/-1 - ioy = iterationOrder( sy ); // +/-1 - - // Determine whether we can avoid blocked iteration... - ord = strides2order( sl ); - if ( iox !== 0 && ioy !== 0 && ord === strides2order( sy ) && K <= MAX_DIMS ) { // eslint-disable-line max-len - // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... - if ( y.accessorProtocol ) { - return ACCESSOR_UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - return UNARY[ K ]( fcn, arr, views, sl, ord === 1, opts ); - } - // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... - if ( K <= MAX_DIMS ) { - if ( y.accessorProtocol ) { - return BLOCKED_ACCESSOR_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, sl, opts ); - } - // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... - if ( y.accessorProtocol ) { - return accessorunarynd( fcn, arr, views, sl, opts ); - } - unarynd( fcn, arr, views, sl, opts ); -} - - -// EXPORTS // - -module.exports = unaryReduceSubarray; diff --git a/lib/nd.js b/lib/nd.js deleted file mode 100644 index f5bcc54..0000000 --- a/lib/nd.js +++ /dev/null @@ -1,150 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -* var ybuf = filled( false, 3 ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major' -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major' -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - ybuf[ io[1] ] = fcn( views, opts ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/nd_accessors.js b/lib/nd_accessors.js deleted file mode 100644 index 44bee90..0000000 --- a/lib/nd_accessors.js +++ /dev/null @@ -1,158 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numel = require( '@stdlib/ndarray-base-numel' ); -var vind2bind = require( '@stdlib/ndarray-base-vind2bind' ); -var zeros = require( '@stdlib/array-base-zeros' ); -var setViewOffsets = require( './set_view_offsets.js' ); -var offsets = require( './offsets.js' ); - - -// VARIABLES // - -var MODE = 'throw'; - - -// MAIN // - -/** -* Performs a reduction over an input ndarray and assigns results to a provided output ndarray. -* -* @private -* @param {Function} fcn - reduction function -* @param {Array} arrays - ndarrays -* @param {Array} views - initialized ndarray-like objects representing sub-array views -* @param {IntegerArray} strides - loop dimension strides for the input ndarray -* @param {Options} opts - function options -* @returns {void} -* -* @example -* var toAccessorArray = require( '@stdlib/array-base-to-accessor-array' ); -* var accessors = require( '@stdlib/array-base-accessors' ); -* var Float64Array = require( '@stdlib/array-float64' ); -* var filled = require( '@stdlib/array-base-filled' ); -* var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); -* var base = require( '@stdlib/ndarray-base-every' ); -* -* // Create data buffers: -* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) ); -* var ybuf = toAccessorArray( filled( false, 3 ) ); -* -* // Define the array shapes: -* var xsh = [ 3, 2, 2 ]; -* var ysh = [ 3 ]; -* -* // Define the array strides: -* var sx = [ 4, 2, 1 ]; -* var sy = [ 1 ]; -* -* // Define the index offsets: -* var ox = 0; -* var oy = 0; -* -* // Create an input ndarray-like object: -* var x = { -* 'dtype': 'float64', -* 'data': xbuf, -* 'shape': xsh, -* 'strides': sx, -* 'offset': ox, -* 'order': 'row-major', -* 'accessors': accessors( xbuf ).accessors -* }; -* -* // Create an output ndarray-like object: -* var y = { -* 'dtype': 'generic', -* 'data': ybuf, -* 'shape': ysh, -* 'strides': sy, -* 'offset': oy, -* 'order': 'row-major', -* 'accessors': accessors( ybuf ).accessors -* }; -* -* // Initialize ndarray-like objects representing sub-array views: -* var views = [ -* { -* 'dtype': x.dtype, -* 'data': x.data, -* 'shape': [ 2, 2 ], -* 'strides': [ 2, 1 ], -* 'offset': x.offset, -* 'order': x.order -* } -* ]; -* -* // Perform a reduction: -* unarynd( base, [ x, y ], views, [ 4 ], {} ); -* -* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); -* // returns [ true, false, true ] -*/ -function unarynd( fcn, arrays, views, strides, opts ) { - var ybuf; - var len; - var set; - var sh; - var iv; - var io; - var N; - var v; - var y; - var i; - var j; - - N = arrays.length; - - // Resolve the output ndarray and associated shape: - y = arrays[ 1 ]; - sh = y.shape; - - // Compute the total number of elements over which to iterate: - len = numel( sh ); - - // Resolve a list of pointers to the first indexed elements in the respective ndarrays: - iv = offsets( arrays ); - - // Cache a reference to the output ndarray buffer: - ybuf = y.data; - - // Cache accessors: - set = y.accessors[ 1 ]; - - // Iterate based on the linear **view** index, regardless as to how the data is stored in memory... - io = zeros( N ); - for ( i = 0; i < len; i++ ) { - for ( j = 0; j < N; j++ ) { - v = arrays[ j ]; - io[ j ] = vind2bind( sh, v.strides, iv[ j ], v.order, i, MODE ); - } - setViewOffsets( views, io ); - set( ybuf, io[1], fcn( views, opts ) ); - } -} - - -// EXPORTS // - -module.exports = unarynd; diff --git a/lib/offsets.js b/lib/offsets.js deleted file mode 100644 index a606628..0000000 --- a/lib/offsets.js +++ /dev/null @@ -1,42 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Resolves index offsets from a list of ndarray-like objects. -* -* @private -* @param {ArrayLikeObject} arrays - list of ndarray-like objects -* @returns {NonNegativeIntegerArray} list of offsets -*/ -function offsets( arrays ) { - var out = []; - var i; - for ( i = 0; i < arrays.length; i++ ) { - out.push( arrays[ i ].offset ); - } - return out; -} - - -// EXPORTS // - -module.exports = offsets; diff --git a/lib/set_view_offsets.js b/lib/set_view_offsets.js deleted file mode 100644 index 32628ce..0000000 --- a/lib/set_view_offsets.js +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Sets view offsets according to a list of index offsets. -* -* ## Notes -* -* - This function skips the second element in the list of index offsets, as that is assumed to correspond to the output ndarray which does not have a corresponding view. Meaning, the list of views is expected to have `N` elements, and the list of index offsets is expected to have `N+1` elements. -* - This function mutates the provides view objects. -* -* @private -* @param {Array} views - list of ndarray-like objects representing ndarray views -* @param {NonNegativeIntegerArray} offsets - list of index offsets -* @returns {Array} updated views -*/ -function setViewOffsets( views, offsets ) { - var i; - var j; - for ( i = 0, j = 0; i < offsets.length; i++ ) { - if ( i === 1 ) { // note: expected to correspond to the output ndarray which does not have a corresponding view - continue; - } - views[ j ].offset = offsets[ i ]; - j += 1; - } - return views; -} - - -// EXPORTS // - -module.exports = setViewOffsets; diff --git a/package.json b/package.json index 5a46cf7..c0ff37e 100644 --- a/package.json +++ b/package.json @@ -3,29 +3,8 @@ "version": "0.0.0", "description": "Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.", "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": { - "test": "make test", - "test-cov": "make test-cov", - "examples": "make examples" - }, + "type": "module", + "main": "./index.mjs", "homepage": "https://stdlib.io", "repository": { "type": "git", @@ -34,50 +13,6 @@ "bugs": { "url": "https://github.com/stdlib-js/stdlib/issues" }, - "dependencies": { - "@stdlib/array-base-indices-complement": "github:stdlib-js/array-base-indices-complement#main", - "@stdlib/array-base-join": "^0.1.1", - "@stdlib/array-base-take-indexed": "^0.2.2", - "@stdlib/array-base-take-indexed2": "github:stdlib-js/array-base-take-indexed2#main", - "@stdlib/array-base-without": "github:stdlib-js/array-base-without#main", - "@stdlib/array-base-zeros": "^0.2.2", - "@stdlib/assert-is-function": "^0.2.2", - "@stdlib/ndarray-base-iteration-order": "^0.2.2", - "@stdlib/ndarray-base-ndarraylike2object": "^0.2.2", - "@stdlib/ndarray-base-numel": "^0.2.2", - "@stdlib/ndarray-base-strides2order": "^0.2.2", - "@stdlib/ndarray-base-to-unique-normalized-indices": "github:stdlib-js/ndarray-base-to-unique-normalized-indices#main", - "@stdlib/ndarray-base-unary-loop-interchange-order": "^0.2.1", - "@stdlib/ndarray-base-unary-tiling-block-size": "^0.2.2", - "@stdlib/ndarray-base-vind2bind": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2", - "@stdlib/utils-define-nonenumerable-read-only-property": "^0.2.2", - "@stdlib/error-tools-fmtprodmsg": "^0.2.2" - }, - "devDependencies": { - "@stdlib/array-base-filled": "^0.2.2", - "@stdlib/ndarray-base-every": "github:stdlib-js/ndarray-base-every#main", - "@stdlib/ndarray-base-to-array": "^0.2.1", - "@stdlib/random-array-discrete-uniform": "^0.2.1", - "tape": "git+https://github.com/kgryte/tape.git#fix/globby", - "istanbul": "^0.4.1", - "tap-min": "git+https://github.com/Planeshifter/tap-min.git" - }, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], "keywords": [ "stdlib", "base", @@ -91,7 +26,6 @@ "accumulation", "subarray" ], - "__stdlib__": {}, "funding": { "type": "opencollective", "url": "https://opencollective.com/stdlib" diff --git a/stats.html b/stats.html new file mode 100644 index 0000000..f044af8 --- /dev/null +++ b/stats.html @@ -0,0 +1,4842 @@ + + + + + + + + Rollup Visualizer + + + +
+ + + + + diff --git a/test/dist/test.js b/test/dist/test.js deleted file mode 100644 index a8a9c60..0000000 --- a/test/dist/test.js +++ /dev/null @@ -1,33 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2023 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var main = require( './../../dist' ); - - -// TESTS // - -tape( 'main export is defined', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( main !== void 0, true, 'main export is defined' ); - t.end(); -}); diff --git a/test/test.js b/test/test.js deleted file mode 100644 index 748ff1d..0000000 --- a/test/test.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2025 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var unaryReduceSubarray = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof unaryReduceSubarray, 'function', 'main export is a function' ); - t.end(); -}); - -// FIXME: add tests